Communication Issues in Heterogeneous Embedded Systems
Enable Device-to-Device Communications
I NTRODUCTIONI n the past two decades, there have been tremendous technology development and com-mercial success in wireless cellular networks.Cellular users are increasing exponentially,spread out all over the world, benefitting from various services including voice, data, and video. Recently, device-to-device (D2D) com-munications underlaying a cellular network infrastructure has been proposed and has attracted much attention [1–3]. D2D underlay-ing a licensed cellular network, which can pro-vide more service guarantees in a controlled environment, enables user equipment (UE) tocommunicate with other nearby UE directly over a D2D link under the cellular network channel resources without extra hops through the central base station. In general, D2D com-munication allows fast access to the radio spec-trum with a controlled interference level andholds the promise of four types of gain: proxim-ity gain, reuse gain, hop gain, and paring gain [3]. Typical D2D communication applications are peer-to-peer (P2P) file sharing, local voice service, video streaming, and content-aware applications.There are paramount challenges and active research activities regarding D2D communica-tions underlaying cellular networks. First, inter-ference management is critical since cellular networks need to manage new interference sce-narios by supporting D2D communications. In cellular networks, traditional cellular UEs (CUEs) can be considered as primary UEs, and additional D2D UEs (DUEs) should not degrade the performance of CUEs. On the other hand, the interference from current cellu-lar networks may also hurt the quality of ser-vice (QoS) requirements of DUEs. Many research aspects are related to interference management, including mode selection,resource allocation, power control, and so on.Second, multihop D2D communication, which allows a UE to be a relay to help other UEs,has not been fully investigated yet. Network coding can be attempted in such scenarios and help improve the throughput of multihop D2D communications underlaying cellular networks.Third, since heterogeneous cellular architecture with a mixed deployment of macro and micro base stations is a key technology in future wire-less systems, coexistence of D2D communica-tions in such heterogenous networks is also worth discussing.This article is organized as follows. First, we give a summary of D2D technology’s merits,challenges, and progress in standards. Then we focus on critical challenges and research aspects in D2D communications underlaying cellular networks: interference management, multihop D2D communications with network coding, and D2D communications in heterogeneous net-works. Specifically, mechanisms such as mode selection, resource allocation, D2D communica-tions with multi-antenna transmission tech-niques, and power control are considered.Finally, performance evaluation in D2D com-munications underlaying cellular networks is provided.A BSTRACTDevice-to-device communication underlaying a cellular network is a promising technology in future wireless networks to improve network capacity and user experience. While D2D com-munication has great potential to improve wire-less system spectral and energy efficiency due to the proximity of communication parties and higher spectrum reuse gain, tremendous work is still ongoing to turn the promising technology into a reality. This article discusses D2D techni-cal challenges as well as standards progress and important research aspects that enable D2D communications underlaying cellular networks.The key research areas addressed include inter-ference management, multihop D2D communi-cations, and D2D communications in hetero-geneous networks. When enabling D2D commu-nications underlaying cellular networks, D2D communications can use either cellular down-link or cellular uplink resources. The two resource sharing modes will create different interference scenarios. The performance evalua-tion on D2D communications underlaying cellu-lar networks under these two different scenarios is provided.Lili Wei, Rose Qingyang Hu, Yi Qian, and Geng WuEnable Device-to-Device Communications Underlaying Cellular Networks:Challenges and Research Aspectsresource allocation by the eNB. When a D2D pair needs to communicate underlaying a cellular network, how to allocate cellular resources to the D2D transmission is critical since the interfer-ence to other primary CUEs should be kept below a certain level while the D2D communica-tion also needs to be fulfilled with quality. Resource allocation should be jointly considered with mode selection, that is, whether the network can allow some channel resources to the D2D pair, and if so, whether some dedicated PRBs or some shared PRBs the D2D pair will obtain; if it is a shared case, which cellular UEs’ resource blocks should be shared with this D2D pair; if it is a dedicated case, how many PRBs should be permitted for this D2D communication.On the other hand, instead of centralized resource allocation, in which the eNBs take full responsibility in controlling/allocating the resources of D2D communications, resource allocation may also proceed in a distributed manner. If D2D communication is favorable between two UEs, the UEs need to sense the network environment, access the cellular resources without causing harmful interference to the CUEs, and inform the eNBs of D2D resource occupations.P OWER C ONTROLPower control is vital in achieving efficient ener-gy usage and interference coordination in wire-less networks. In D2D enabled cellular networks,we consider CUEs as the primary users and theirquality-of-service (QoS) requirements are deliv-ered with priority. Hence, the power control insuch a network will first intend to control thetransmission power of DUEs such that theinterference from DUEs to CUEs can be throt-tled [7]. Power control can be centrally opti-mized such that the overall network throughputis maximized. which means in some cases, wemay need to lower the power of eNBs in thedownlink given that the CUE performance willnot be degraded, such that the transmission ratesof DUEs will improve and the overall sum-rateof all network UEs increases accordingly. Inaddition, power control mechanism can be con-sidered jointly with mode selection and resourceallocation to optimize the network performance.Power efficiency or energy efficiency for D2Dcommunications underlaying cellular spectrum isalso worthy of discussion.D2D C OMMUNICATIONS WITHM ULTI-A NTENNA T RANSMISSION T ECHNIQUESMulti-antenna transmission techniques [8] canbe incorporated into D2D communicationsunderlaying cellular networks to further avoidinterference among different UEs. When DUEsand CUEs are sharing the same LTE resources,with multiple antennas, we get an additionalspace dimension, besides time and frequencydimensions, to cope with interference. The dif-ference of design beamforming vectors for D2Dcommunications underlaying cellular networksand the traditional cellular networks lies in that,in D2D communication environment, CUEs andDUEs may be considered as two groups of userswith CUEs as primary users. The design criteri-on may aim to lessen interference among CUEsor from DUEs to CUEs, etc.In [9] we discussed the scenario that multipleCUEs and multiple DUEs co-exist in the cellularnetwork. The eNB is equipped with multipleantennas, hence it can formulate precoding vec-tors in the downlink transmission to CUEs withdifferent criteria. For the conventional beam-forming method, the precoding vector of a CUEwill lie in the direction of its own channel vector.For the zero-forcing (ZF) beamforming method,to cancel out inter-UE interference, the informa-tion data of a CUE is designed to be transmittedin the null space of the channels of all otherCUEs. If we consider ZF beamforming to cancelout the interference caused by the eNB trans-mission to DUEs, we can design a CUE’s pre-coding vector so that its data is transmitted inthe null space of DUE channels. Based on thedifferent multi-antenna transmission techniques,D2D pair associations and precoding vectors canbe jointly optimized to maximize the overall sys-tem throughput. The D2D pair associationsshould also keep the interference from DUEs toCUEs below a certain level so that the signal-to-noise-plus-interference ratio (SINR) of CUEswill meet the requirements. Further studies canbe extended with robust beamforming design forD2D communications underlying cellular net-works.M ULTI-H OP D2DC OMMUNICATIONS WITHN ETWORK C ODINGIn general, we think of D2D communications astwo UEs communicating directly without goingthrough eNBs. In fact, D2D communications canbe further broadened to the multi-hop D2Dcommunications in which a UE may help otherUEs communicate with each other, or assistother UEs to communicate with eNBs.For example, as one scenario of multi-hopD2D communications, if multiple UEs arerequesting the same contents from the eNB, theycan first form cooperative clusters according tothe geometry to achieve a higher energy efficien-cy and spectrum efficiency during content distri-bution. I n the first step, the eNB will firsttransmit the contents to the cluster heads. In thesecond step, each cluster head will in turn multi-cast the contents to other UEs within the clusterthrough D2D links. The eNB can stay silent dur-ing the second step and hence keep the networkenergy efficient. The application of this multi-hop D2D communication scenario includesvideo streaming of most popular programs, forinstance during the FIFA World Cup, when mul-tiple UEs are watching the same football match.In such multi-hop D2D communications, net-work coding [10], which is a promising mecha-nism in cooperative networks to improvethroughput, can be applied. Originally designedfor wired networks, network coding is a general-ized approach that breaks the traditionalassumption of simply forwarding data, and allowsintermediate nodes to send out functions of theirreceived packets, by which the multicast capacityC ONCLUSIONSIn this article critical D2D communication chal-lenges and important research aspects that enable device-to-device communications underlaying cel-lular networks are discussed. The topics addressed include interference management, multi-hop D2D communications with network coding, and D2D communications in heterogeneous networks. Mechanisms such as mode selection, resource allocation, D2D communications with multi-antenna transmission techniques, and power con-trol are illustrated in detail. Performance evaluation based on PPP distributions of CUEs and DUEs is provided. Effective D2D communi-cations can be enabled in a cellular network through proper radio resource sharing, interfer-ence management and power control mechanisms.A CKNOWLEDGMENTThis work was supported in part by US National Science Foundation (NSF) grants ECCS-1308006, ECCS-1307580, and CNS-1065069.R EFERENCES[1] K. Doppler et al., “Device-to-Device Communications asan Underlay to LTE-Advanced Networks,” IEEE Com-mun. Mag., vol. 47, no. 12, Dec. 2009, pp. 42–49. [2] L. Lei et al., “Operator Controlled Device-to-DeviceCommunications in LTE-Advanced Networks,”IEEEWireless Commun., vol. 19, no. 3, June 2012, pp.96–104.[3] G. Fodor et al., “Design Aspects of Network AssistedDevice-to-Device Communications,” IEEE Commun.Mag., vol. 50, no. 3, Mar. 2012, pp. 170–77.[4] A. F. Molisch, “Wireless Communications,” ISBN: 978-0-470-74187-0, John Wiley & Sons Ltd., 2011.[5] C. H. Yu et al., “Resource Sharing Optimization rorDevice-to-Device Communicationunderlaying CellularNetworks,” IEEE Trans. Wireless Commun., vol. 10, no.8, Aug. 2011, pp. 2752–63.[6] M. Zulhasnine, C. Huang, and A. Srinivasan, “EfficientResource Allocation for Device-to-Device Communica-tion Underlaying LTE Network,” Proc. IEEE 6th Int’l.Conf. Wirless and Mobile Computing, Ontario, Canada,Oct. 2010, pp. 368–75.[7] C. Yu et al., “On the Performance of Device-to-DeviceUnderlay Communication with Simple Power Control,”Proc. IEEE Vehic. Tech. Conf., Barcelona, Spain, Apr.2009.[8] Q. H. Spencer et al., “An Introduction to the Multi-UserMIMO Downlink,” IEEE Commun. Mag., vol. 42, no. 10,Oct. 2004, pp. 60–67.[9] L. Wei et al., “Device-to-Device (D2D) CommunicationsUnderlaying MU-MIMO Cellular Networks,” Proc. IEEEGlOBECOM, Atlanta, GA, Dec. 2013.[10] R. Ahlswede et al., “Network Information Flow,” IEEETrans. Info. Theory, vol. 46, no. 4, July 2000, pp.1204–16.[11] K. Lu et al., “On Capacity of Random Wireless Net-works with Physical-Layer Network Coding,” IEEE JSAC,vol. 27, no. 5, June 2009, pp.763–72.[12] S. Fu et al., “Cooperative Network Coding for WirelessAd-Hoc Networks,” Proc. IEEE Globecom, Washington,DC, Nov. 2007.[13] R. Q. Hu and Y. Qian, Heterogeneous Cellular Net-works, John Wiley & Sons Ltd., 2013.[14] Q. Li et al., “On the Optimal Mobile Association inHeterogeneous Wireless Relay Networks,” Proc. IEEEINFOCOM, Orlando, FL, March, 2012.[15] M. Haenggi et al., “Stochastic Geometry and RandomGraphs for the Analysis and Design of Wireless Net-works,” IEEE JSAC, vol. 27, no. 7, Sept. 2009, pp.1029–46.B IOGRAPHIESL ILI W EI[S’05, M’11] (liliwei@) received B.S. andM.S. degree from Shanghai Jiao Tong University, China in1997 and 2000, Ph.D. degree from State University ofNew York at Buffalo in 2008, respectively. From 2000 to2001, she worked as a R&D engineer in Wuhan ResearchInstitute of Posts and Telecommunications, China. Thenshe was with the Chinese Academy of Telecommunica-tion Technology, Beijing, China and worked on the devel-opment of 3G TD-SCDMA wireless communicationsystems until August 2003. After pursuing Ph.D. degree,She has worked as Postdoc Research Fellow in State Uni-versity of New York at Buffalo, Shanghai Jiao Tong Uni-versity and now in Utah State University. Her researchinterests are in communication theory and signal pro-cessing, including wireless cooperative networks, spread-spectrum theory and applications, and practicalcommunication systems.R OSE Q INGYANG H U[S’95, M’98, SM’06] (rosehu@)received a B.S. degree in Electrical Engineering from Uni-versity of Science and Technology of China, a M.S. degreein Mechanical Engineering from Polytechnic Institute ofNew York University, and a Ph.D. degree in Electrical Engi-neering from the University of Kansas. From January 2002to June 2004 she was an assistant professor with theDepartment of Electrical and Computer Engineering atMississippi State University. She also has more than 10years of R&D experience with Nortel, RIM and Intel as atechnical manager, a senior wireless system architect, anda senior research scientist. Currently she is an associateprofessor with the Department of Electrical and ComputerEngineering at Utah State University. Her current researchinterests include next-generation wireless communications,wireless network design and optimization, green radios,multimedia QoS/QoE, communication and informationsecurity, wireless system modeling and performance analy-sis. She has published extensively and holds numerouspatents in her research areas. She is currently serving onthe editorial boards for IEEE Wireless CommunicationsMagazine, IEEE Internet of Things Journal, IEEE Communi-cations Surveys and Tutorials. She has also been a 6-timeguest editor for IEEE Communications Magazine, IEEEWireless Communications Magazine, and IEEE NetworkMagazine. He received IEEE Globecom 2012 Best PaperAward. She is a member of Phi Kappa Phi and Epsilon PiEpsilon Honor Societies.Y I Q IAN(yqian@) [M’95, SM’07] is an associate pro-fessor in the Department of Computer and ElectronicsEngineering, University of Nebraska-Lincoln (UNL). Prior tojoining UNL, he worked in the telecommunications indus-try, academia, and the government. Some of his previousprofessional positions include serving as a senior memberof scientific staff and a technical advisor at Nortel Net-works, a senior systems engineer and technical advisor atseveral startup companies, an assistant professor at theUniversity of Puerto Rico at Mayaguez, and a seniorresearcher at the National Institute of Standards and Tech-nology. His research interests include information assur-ance and network security, network design, networkmodeling, simulation and performance analysis for nextgeneration wireless networks, wireless ad hoc and sensornetworks, vehicular networks, broadband satellite net-works, optical networks, high-speed networks, and theInternet. He has a successful track record in leadingresearch teams and publishing research results in leadingscientific journals and conferences. Several of his recentjournal articles on wireless network design and wirelessnetwork security are among the most accessed papers inthe IEEE Digital Library. He is a member of ACM.G ENG W U[SM’04] (geng.wu@) received the B.Sc.degree in electrical engineering from Tianjin University,Tianjin, China, and the Ph.D. degree in telecommunicationsfrom Universit Laval, Quebec City, Canada. He is currentlyChief Scientist and Director of Standards and AdvancedTechnology with the Mobile and Communications Group,Intel Corporation. Prior to joining Intel, he was Director ofWireless Architecture and Standards with Nortel Networks,where he was responsible for wireless technology andstandards development. He has over 20 years of researchand development experience in the wireless telecommuni-cation industry, extensively contributed to Second-, Third-,and Fourth-Generation air interface technologies and net-work architecture development. He is the holder of 28 U.S.patents. His current research interests include mobile com-puting and communication platforms, heterogeneous net-works and cloud-based radio access network,next-generation air interface technologies, and advancedmobile services and applications.。
西方翻译史概括
Translation and GenderHistorical BackgroundThe women's Movement and the Idea of GenderSimon de Beauvoir wrote in 1949"on ne nait pas femme, on le devient". E.M.Parshley translated this in 1953 as "one is not born, but rather becomes a woman". Beauvoir suggests that a girlbaby is turned into a woman by the society she grows up in and in response to the expectations that society has of women. The final product 'woman' is a result of education and conditioning, and differs according to the dominant influences she is subject to in the culture.Gender refers to the sociocultural construction of both sexes. Feminist thinkers of the late 1960s and early 1970s developed the term in the interests of examining and understanding women's socialized difference from men, and their comitant cultural and political powerlessness.Women and LanguageMany feminists think that language is not only a tool for communication but also a manipulative tool.Two different approaches to questions about women and language: The reformormist approach: view conventional language as a symptom of the society that spawned it. The radical approach: view conventional language as an important cause of women's oppression, the medium through which women were taught and came to know their subordinate place in the world. (Cameron 1985)The women's movement of the late 1960s and early 1970s focused on two aspects of women's difference:First, it tried to show how women's difference from men was in many ways due to the artificial behavioural stereotypes that come with gender conditioning. Second, the movement de-emphasized differences between women, stressing instead shared experiences, their commonality, their solidarity.Gender and the Practice of TranslationGender awareness in translation practice poses questions about the links between social stereotypes and linguistic forms, about the politics of language and cultural difference, about the ethics of translation, and about reviving inaccessible works for contemporary readers.It highlights the importance of the cultural context in which translation is done.Experimental Feminist Writing and Its TranslationThe radical feminist writing of the 1970s was experimental. It was radical as it sought to undermine, subvert, even destroy the conventional everyday language maintained by institutions such as schools and universities, publishing houses and the media, dictionaries, writing manuals, and the 'great works' of literature. Thus, they took on the radical position of attacking language itself, rather than just the messages carried by the language.Radical feminist writing in the late twentieth century has been experimental in that it explores new ground, seeking to develop new ideas and a new language for women. The theory is that the language women have at their disposal will influence their creativity, affecting their ability to think in revolutionary terms and their capacity to produce new work.Experiments have blossomed in every Western European and North American country, and in all languages due to the fact that writers are deconstructing different languages as well as different cultures, which require feminist attention in different places.Translating Experiments with LanguageWhen the grammar of a language such as French dictates that nouns, adj. and participles need to be gender-identified, feminist writers can subvert this gender requirement and the symbolic system that underlies it by applying the grammar system differently. This could mean feminizing words to give them new meanings. Similarly, when the syntax of a language or its conventions of style are too restrictive for women's new vision. the writer can change it.Assertive Feminist TranslationNo act of writing or translation is neutral and rewriting in the feminine is a conscious act that puts its cards on the table from the very beginning . Its project is to imbue translation praxis with feminist consciousness. Translation thus becomes a political activity that has the objective of making women visible and resident in language and society.Issues of sexism or women's silencing need not only be pointed out, they need to be solved with deliberate feminist intervention that redresses the imbalance and places women directly into the language.Descriptive Translation Studies and and Poly-system Theory Describing TranslationWhat confronted the translation researchers first is the relationship between a text and one or more translations of it. They try to analyze it from the perspective of description and empirical assessment.The main differences between systematic attempts at description concern approach and procedure. Some are source-text based, while others treat the source and target text on an equal basis.Toury’s AT TheoryIn 1980, Toury argued that the tertium comparatist should take into account the unequal status of a translation in relation to its source. The tertium comparatist, which Toury calls the A T or Adequate Translation, results from an analysis of the source text. A T is a hypothetical construct consisting of an “explicitation of [source text] textual relations and functions”(Descriptive Translation Studies and Beyond 1980:116)A T embodies the principle of a wholly retentive, source-text-oriented translation. This principle, which also constitutes a practical translation strategy, is termed ‘adequacy’. It refers to a mode of translation “which realizes in the target language the textual relationships of a source text with no breach oThe comparison between textual relations and functions presented in the source text and the target text:The identification of textual relations and functions in the source text and the formulation of the A TMapping target-text units on the A T and on the corresponding source-text unitsMeasuring shifts and deviations between target text, source text and A T so as to be able to characterize the overall relation between the translation and its sourceToury’s NormsNorms：external and socio-cultural constraintsThey are seen as “performance instructions”, both in a general sociological sense and, with reference to communication and translation, in the sense of controlling linguistic usage.Norms operate at the intermediate level between competence and performance. Competence stands for the set of options translators have at their disposal. Performance refers to the options actually selected Decisions and Norms:Jiri Levy’s ‘generative model’emphasized that at every level the translator had to choose one option from among a set of alternatives, in the knowledge that every decision will affect all subsequent decisions.The process covers everything from the selection of a text to be translated, via the overall orchestration at macro-level, down to individual sentence constructions, word choice, punctuation marks and even spelling.Preliminary norms（初步准则）, which concerns such things as the choices of the text to translate, or the decision to work directly from the original language or from an existing translation in another language, the decision to translate into the native or into a second or third languagethe initial norm（首要准则）, which governs the translator’s choice between two polar alternatives regarding the translation’s overall orientation, one which leans as far as possible to the source text, the other subscribing to usage in the receptor culture; the first pole Toury calls that of ‘adequacy’, the other that of ‘acceptability’③operational norms（操作准则），which guide decision-making during the actual business of translating;here Toury distinguishes between.Matricial norms（母体规范）, which help determine the macro-structure of the text and govern decisions concerning translating all or part of the source text, division into chapters, acts, stanzas, paragraphs and the like. Texutual-linguistic norms（文本规范）, which affect the text’s micro-level, the detail of sentence construction, word choice, the use of italics or capitals for emphasis, and so on.Andrew Chesterman’s NormsHis approach is descriptive.Chesterman’s discussion covers social, ethical and technical norms of translationThe social norm regulate interpersonal coordinationThe ethical norms : translators’wish to uphold the values of clarity, truth, trust and understandingThe technical norms: relating the four values(clarity, truth, trust, understanding)Process(or production) norm, which operate at a lower level than expectancy norms, regulate the translation process itself.T he accountability norm,which is ethical in nature, assumes that translators owe loyalty to the original writer, to the commissioner of the translation job, to themselves, and to their clients and prospective readers.The communicative norm is social in character and stipulates that translators should act in such a way as to optimize communication, as required by the situation, between all the parties involved.The relation norm urges the translator to ensure that “an appropriate relation of relevant similarity is established and maintained between the source text and the target text”Norm TheoryNorm refers to both a regularity in behavior and to the underlying mechanism which accounts for this regularity.The mechanism is a psychological and social entity. It mediates between the individual and the collective, between the individual’s intentions, choices and actions, and collectively held beliefs, values and preferences.Poly-system TheoryIt was developed in the 1970s by the Isreali scholar Itamar Even-Zohar brorrowing ideas from the Russian Formalists of the 1920s.Even-Zohar emphasizes that translated literature operates as a system: in the way the TL selects works for translation. in the way translation norms, behaviour and policies are influenced by other co-system According to Shuttleworth and Cowie:The poly-system is conceived as a heterogeneous, hierarchized conglomerate (or system) of systems which interact to bring about an ongoing, dynamic process of evolution within the poly-system as a whole.The hierarchy referred to the positioning and interaction at a given historical moment of the different strata of the poly-system.This 'dynamic process of evolution' is vital to the poly-system, indicating that the relations between innovatory and conservative systems are in a constant state of flux and competition.The position of translated literature is not fixed due to the flux.It may occupy a primary or a secondary position in the poly-system. If it is primary, 'it participates actively in shaping the centre of the poly-system'(Even-Zohar 1978/2000:193)Even-Zohar gives three major cases when translated literature occupies the primary position:when a 'young' literature is being established and looks initially to 'older' literatures for ready-made models when a literature is 'peripheral' or 'weak' and imports those literary types which it is lackingwhen there is a critical turning point in literary history at which established models are no longer considered sufficient, or when there is a vacuum in the literature of the country. (Jeremy Munday 2010:112) If translated literature assumes a secondary position, then it represents a peripheral system within thepolysyetem. It has no majoy influence over the central system and even becomes a conservative element, preserving conventional forms and conforming to the literary norms of the target system.Even-Zohar suggests that the position occupied by translated literature in the polysystem conditions the translation strategy.If it primary, translators do not feel constrained to follow target literature models and are more prepared to break conventions. They often produce a TT that is a close match in terms of adequacy, reproducing the textual relations of the ST.If it is secondary, tranlators tend to use existing target-culture models for the TT and produce more 'non-adequate' translations.The advantages of poly-system:Literature itself if studied alongside the social, historical and cultural forcesEven-Zohar moves away from the isolated study of individual texts toward the study of translation within the cultural and literary systems in which it functionsThe non-prescriptive definition of equivalence and adequacy allows for variation according to the historical and cultural situation of the text.The criticisms of poly-system theory:overgeneralization to 'universal laws' of translation based on relatively little evidencean over-reliance on a historically based 1920s' Formalist model which might be inappropriate for translated texts in the 1970s.the tendency to focus on the abstract model rather than the 'real-life' constraints placed on texts and translators the question as to how far the supposed scientific model is really objectivity.Even-Zohar suggests that the position occupied by translated literature in the polysystem conditions the translation strategy.If it primary, translators do not feel constrained to follow target literature models and are more prepared to break conventions. They often produce a TT that is a close match in terms of adequacy, reproducing the textual relations of the ST.If it is secondary, translators tend to use existing target-culture models for the TT and produce more 'non-adequate' translations.。
(英文)SCA：演变与状态更新
28 / October 2005 Reprinted from Military EMBEDDED SyStEMSOriginally developed for the military’s Joint Tactical Radio System (JTRS) program of Software Defined Radios (SDRs), the Software Communications Architecture (SCA) middleware is the key component to abstracting the underlying hardware from interoperable and programmable waveforms. The SCA, in effect, is what reprograms the radios to facilitate their reconfigurabil-ity. While the SCA remains strongly influenced by the JTRS pro-gram and the military, it’s now also being considered for use in commercial and civilian applications. Throughout time, the SCA has evolved as users (civilian and military alike), industry com-mittees, and complementary standards weigh in on SCA features and capabilities.The SCA is a common specification standard and component-based software framework/architecture for SDR. The SCA is designed to facilitate waveform portability between different platforms and to leverage commercial standards, frameworks, and architectures to reduce development cost and improve reuse. A reas addressed by the SCA include waveform download, interoperability, operation and deployment on SDR devices, A PIs (such as network layers, security, and common devices), and common component information.While there are many interpretations of SDR, for the purposes of this article, external devices and the infrastructure composing the software bus will not be included as their future is independent of the SCA (for instance, they may be addressed by different stan-dards bodies or deal with hardware migration). Instead, we will address the SCA by categorizing it into divisions of infrastructure, waveform support, services, device interfaces, heterogeneous pro-cessor, and security.There are many permutations for a future SCA based on antici-pated and existing commercial and government developments. To achieve future goals, it’s key to address the challenges in future SCA development, commercialization, and adoption, and to sum-marize the current state of the SCA and future recommendations. Related commercialization and government standardization activ-ities will certainly also affect the SCA efforts.SCA evolutionSDR has a range of meanings today, depending on the types and number of hardware components that are replaced or upgraded by software. For simplicity, SDR is a term coined to describe a radio with a software-based physical layer that:The SCA originated with the JTRS primarily to support SDR waveform portability for a new family of SDR tactical radios for the US military. The Software Defined Radio Forum (SDRF) assisted the JTRS Joint Program Office (JPO) in developing this open frame-work for SDRs, beginning with version 0.9 to the current version 3.0 (see /sections/technicalinformation/fset_techni-cal_sca.html) with its associated Application Program Interface (API), Specialized Hardware and Security Supplements. The Specialized Hardware Supplement is the main addition to SCA 3.0, which includes other improvements such as the elimination of reference counting and security supplement enhancements.As the SDRF continues to support development of the SCA, it has sponsored the development of both an Open Source Reference Implementation (OSRI) for an SCA-compliant Core Framework (CF) as well as a compliant waveform based on FM3TR. The CF, based on a hybrid Java and C implementation, is available to SDRF members. An FM3TR waveform project is expected for completion later this year; in addition, the SDRF has developed requirements, use cases, Requests For Information (RFI), and Requests For Proposal (RFP). Typically, these technical products are voted and approved by the SDRF, then transferred via for-mal liaisons to other organizations such as the JTRS JPO and the Object Management Group (OMG), an object-oriented software standards organization.For the last three years, SCA evolution has taken a parallel com-mercialization path in the Software Based Communications Domain Task Force () within the OMG. In this forum, the domain-independent portions of the SCA, the bulk of the SCA, such as Lightweight Logging, Lightweight Services, Lightweight CORBA Component Model, Smart Antennae API, Digital Intermediate Frequency API, Deployment and Configuration of Components, and several Security Specifications, are in various phases of the standardization process as separate specifications. Development of these separate specifications allows commercial participation in related tooling and infrastructure.Future SCA revisions should decrease in size and complexity as these OMG domain-independent specifications are completed and used as SCA references. This trend has already begun as the Lightweight Logging API was removed from the SCA, referenc-ing the completed OMG version.Reprinted from Military EMBEDDED SyStEMS October 2005 / 29The OMG strives for SCA compatibility with its own software radio domain-specific version. Synchronization of OMG soft-ware radio specification improvements with the SCA has been achieved through liaisons and OMG member participation in the JTRS SCA Technical Advisory Group (TAG) revision process.Existing SCA divisionsTo simplify the categorization of changes, the SCA can be thought of in terms of current work and divisions as depicted in Figure 1. The current SCA 3.0 infrastructure manages the hardware radio components deployment by configuring devices and making sure they are ready, providing a standard store for configuration files, machine state, user attributes, and functional software, and offer-ing a waveform structure, control, and binding framework for het-erogeneous processors.While not specifically addressing a waveform API, the SCA API supplement is given to support the portability of applications and interchangeability of devices; there is a specialization of the API derived from Cluster 1, a large SCA-compliant JTRS program. The current SCA assumes services that are provided by CORBA, for example, event and time services, and adds a logging service.Device APIs, considered peripherals to the SDR, are also pro-vided as an SCA supplement and at this time, an Antennae API is the only such supplement provided.A standard method to access security functions such as encryp-tion, authentication, transmission security (TRANSEC), and nonrepudiation, is specified in an SCA Security Supplement. Because of the nature of this technology, specializations exist for each JTRS program. In addition, there exists a parallel Air Force/NSA Multiple Independent Levels of Security (MILS) effort to combine the best of FAA DO-178B Common Criteria’s security technologies, so as to provision secure services to embedded real-time, high-assurance platforms.Parallel OMG standards plans and initiatives for the security func-tions and specifications are depicted in the OMG SCA Security Roadmap in Figure 2. A Specialized Hardware Specification SCA Supplement, available for SCA 3.0, specifies how to improve porta-bility of software for processing elements other than general-purpose processors, including a Hardware Abstraction Layer (HAL) for deploying on heterogeneous processors.Forecasted SCA divisionsUsing the same divisions previously identified in Figures 1 and 2, Figure 3 shows a potential SCA evolution with possible choices. SCA changes occur through a Change Proposals (CPs) process and are reviewed though a Technical Advisory Group (TAG) and Change Control Board process. For instance, SCA 3.1 alreadyFigure 1Figure 2C an be ptr from SCA Ptr from SCARevised SCA SHSFigure 3completed in draft form, includes CP289, detailing a Component Portability Specification (note CP289 was not accepted yet).At this date, the OMG version of the Software Radio Specification is in the Finalization Task Force stage. This specification contains only the radio domain and waveform API portions of the specifi-cation, with the component model separated into different speci-fications that describe both the Deployment and Configuration of Components and Lightweight CORBA Component Model currently in the Revision Task Force stage. The SDRF is making additional progress with a new Waveform API contracted research and development project expected to begin in September, partially based on an OMG Software Radio Specification Waveform API Subset document. For the present, synchronization of the OMG and JTRS versions of the Software Radio specifications has been through OMG member participation in the JTRS CP process. There are two new device-related specifications in process. The first is a Smart Antennae API Specification, with parallel efforts in both the SDRF and OMG. The second is an OMG Digital Intermediate Frequency (DIF) API Specification providing a stan-dard API between tuners and the computer(s) hosting the rest of the software radio logic. This DIF specification is the softwareanalog of the hardware standard driven through the () standards group.As previously mentioned, the OMG Lightweight LoggingSpecification has been finalized, serving as an SCA reference.The closest services specification to finalization is the OMGLightweight Services Specification, offering a further reductionin SCA complexity.The OMG Security Specification roadmap (refer back to Figure 2)is still in its initial phases; the first two specifications on thisroadmap, the Core and Key Management Specifications, arein the initial submission stage. The OMG will standardize onthe black, crypto, and red processing described in Figure 4.Common security requirements are combined into this SecuritySubsystem Core to describe the overlap in one specification. TheSecure Audit and Authentication RFPs are complete, with initialsubmissions in work; the rest of the OMG security submissionsin Figure 2 will follow. In the meantime: 1) There are JTRS/NSAplanned upgrades to the SCA Security Supplement; and 2) theJoint Program Executive Office (JPEO) is putting together anInformation Assurance team to plan upcoming security specifica-tion update and implementation testing.Tuning in the futureIf the trend to replace SCA sections with domain-independentportions continues, tool vendor support will increase. In addi-tion, the SCA framework will be smaller, require less testing, andeventually support ultra lightweight deployments in small andlow-power consumption devices. The OMG SWRadio domain-specific specification will, in the short term, contribute to the SCAthough the JTRS SCA change process. The progression fromSCA 3.0 to SCA 3.1 will support true waveform component por-tability over heterogeneous processors.Commercial SCA adoption is still hampered by many factors suchas tool and predefined component availability. Future integration ofSCA and commercial Software Defined basestation specificationsJeff Smith received his Ph.D. from NortheasternUniversity in computer systems engineering, hisMS in engineering management from SouthernMethodist University, his MS in computerscience from East Texas State University, andhis BS in computer systems engineering fromthe University of Massachusetts. He has a 30-year track recordin the acquisition, management, research, and development ofadvanced development/technology programs and heads a con-sulting company, Composable Logic, supporting SCA Technica.Figure 430/ October 2005 Reprinted from Military EMBEDDED SyStEMSReprinted from Military EMBEDDED SyStEMS October 2005 / 31He is one of three co-chairs of the OMG Software-Based Communications Task Force and participates with the OMG Ontology working group. His primary expertise is in modeling/formal methods and applied complex systems (multi-sensor fusion or software radio applications).For more information, contact Jeff at:Composable Logic PO Box 3148Nashua, NH 03061-3148Tel: 603-566-0124Fax: 603-222-2098E-mail: jesmith@ Website: David Murotake received his SB in electrical engineering, SB in English literature and cre-ative writing, SM in electrical engineering and computer science, and a Ph.D. in management of technological innovation from MIT. With more than 30 years of engineering and managementexperience at the US Army, RCA, GE, Lockheed, and Mercury Computer, he founded SCA Technica, Inc. in 2002. SCA Technica specializes in research and development of high-assurance SDR and CR and developed the High Assurance Wireless Computing System (HAWCS™) for protecting SDR and wireless computers from blended radio and Internet “hacking” attacks. A member of the SDRF board of directors, Murotake chairs its markets committee and is its Technical Committee’s past vice-chair. He is founder and chair of numerous SDR working groupsand special interest groups, including the Base Station WG and R & D WG.For more information, contact David at:SCA Technica, Inc.PO Box 3148Nashua, NH 03061-3148Tel: 603-321-6536Fax: 603-222-2098E-mail: dmurotak@ Website: Antonio Martin holds a bachelor’s degree from the University of Maine in computer science and is pursuing a master’s, certified by the Committee on National Security Systems, in computer sci-ence with a concentration in security at Boston University. Tony has eight years experience inthe fields of biometrics, image processing, scalable distributed database and transaction processing, and network and system security. He is a participant at the OMG SW Radio FTF .For more information, contact Antonio at:SCA Technica, Inc.PO Box 3148Nashua, NH 03061-3148Tel: 603-321-5220Fax: 603-222-2098E-mail: tony.martin@Website: Quick interchangeability and expansion Structural heat sinks and heat pipes w w w .r t d .c o m。
Customer_Relationship_Management_in_the_Automotive_Industry_Solution_Brief
CUSTOMER RELATIONSHIP MANAGEMENT IN THE AUTOMOTIVE INDUSTRYHow to Gain a Competitive Edge by Knowing Your Customers and Transforming that Knowledge into Successful Marketing Strategies for Future GrowthFaced with the increasingly complex and competitive environment that characterizes the automotive industry – with challenges ranging from tighter profit margins to new entrants in the new-vehicle and aftermarket service business – original equipment manufacturers (OEMs) and dealers are turning more aggressively to customer relationship management (CRM) to help attract new customers, increase brand loyalty, reduce costs, increase efficiency, and maintain a competitive advantage.Today’s automotive consumers are increasingly well-informed and have an unprecedented level of choice in the marketplace.Customer loyalty is no longer a given and forward-looking auto-motive companies have to work harder than ever to earn and retain it. To respond to high customer expectations, companies are finding they have to use both traditional and emerging chan-nels to deliver more effective, efficient, and profitable marketing,sales, and customer service.To truly get to know and understand their customers, automo-tive companies are looking for ways to gather and analyze vital data about their customers, their vehicles, and their transactions with dealers. Only then can they effectively match their products and service offers with the customers they want to target. So companies need to be able to track customer behaviors and then to link that information to not only the production scheduling process – to build the right products now – but also to the prod-uct development cycle – to bring new products to market faster.And because OEMs and dealers now often need to collaborate closely, they need to be able to share information with greater visibility in real time.The automotive industry faces significant challenges caused by frequent disconnects in communication between manu-facturers, dealers, and end customers. The mySAP™ Cus-tomer Relationship Manage-ment solution helps increase revenues by enabling firms to manage communications across all sales and marketing channels, collaborate with dealers, interact with cus-tomers, and grow brand equity and customer loyalty. The integrated solution offers global insight, low imple-mentation costs, and lowtotal cost of ownership.SAP Solution Brief SAP for AutomotiveActing on these imperatives is hampered by the reality that heterogeneous systems preclude a single view of the customer or vehicle, resulting in a poor understanding of customer prefer-ences, higher costs, decreased responsiveness, and eroding brand equity. A single, integrated solution can help connect disparate sources of relevant data and lead to a better understanding of the automotive customer and to improved implementation and execution of the processes involved in serving that customer. The SAP for Automotive solution portfolio can help. With the mySAP™ Customer Relationship Management (mySAP CRM) solution – part of SAP for Automotive – companies like yours can integrate both SAP® and non-SAP solutions to improve rela-tionships with customers and dealers, enhance communication, and increase profitability. In addition, the SAP solutions can help global companies understand and adapt to shifting demands and service preferences across all regions.The mySAP CRM solution supports key automotive business processes including brand and customer management, vehicle life-cycle management, leasing and financing, dealer channel management, vehicle sales and distribution, interaction center, service parts management, warranty management, dealer busi-ness management, and analytics and business process visibility. This solution brief focuses on the core CRM processes. Enabling Collaborative, Customer-Centric Business SAP for Automotive is an industry-specific set of solutions that enables you to deliver customer value, enhance capabilities across the sales and service value chain, and achieve profitable growth. With mySAP CRM, supported by the SAP NetWeaver®platform, you can connect all resources – from suppliers to OEMs to dealers to sales offices – in a closed-loop customer and vehicle interaction cycle. SAP NetWeaver also provides powerful business intelligence so that you can integrate analytics into your customer-focused business processes. Real-time business insight helps you make quick, informed decisions while capa-bilities for capturing and mining relevant data enable you to measure, predict, plan, and optimize customer relationships with greater effectiveness then ever before.The SAP solution delivers functionality throughout the cus-tomer engagement and vehicle life cycle, enabling the full range of CRM processes and providing all the capabilities you need –particularly in the crucial areas of channel management, brand and customer management, customer interaction center, and roadside assistance.Better Communication Across All ChannelsLack of communication between OEMs and their end customers is a pervasive problem. Contact between OEMs and customers is limited and often involves a customer-initiated problem or complaint. Or customers may hear only indirectly from the OEM in the form of marketing campaigns. So a key IT process requirement in the automotive industry is to facilitate effective communications between OEMs and their dealers and – through the dealers – with the customers who buy the vehicles.The mySAP CRM solution makes channel integration across entire networks possible in a cost-effective manner and supports key business processes. Sales and service organizations can give dealer employees access through portal applications and provide access to dealer management systems through Web-based ser-vices. For example, the portal solutions help enable business processes, whether it’s a dealer employee placing or confirming orders with the OEM or whether it’s a national sales company representative viewing vehicle inventories, flooring cost, or aging. Using contact and vehicle management tools, you can incorporate end-customer information and history into sales processes, providing partners and brand owners with a single, comprehensive view into all the information relevant to sales accounts. You can also use the mySAP CRM solution to recruit, train, and collaborate with dealers.Vehicle marketing and sales is at its best when OEMs and dealers collaborate in the process. With mySAP CRM, OEMs and dealers can run collaborative campaigns using tools that help them distribute marketing materials, manage sales collateral, and inte-grate fulfillment. In addition, powerful lead and opportunity management tools allow you to capture, route, and manage sales leads so that each lead is directed to the appropriate chan-nel and dealer. For central campaigns, you can create rules to manage data access, giving you greater choice, flexibility, and control.Ultimately, mySAP CRM helps OEMs better manage dealer and marketing partner relationships. This leads to a better under-standing of your partners’ business – and of the end customers they serve.Build Brand Equity and Customer LoyaltyGiven the constraints of maximizing profits in other areas of the industry – with constant pressure on margins and the struggle for market share – a vitally important trend is the optimization of existing customer relationships and efforts to gain new customers through the creation of unique brand images.The mySAP CRM solution helps you manage structured but highly individualized customer treatment initiatives across multiple communication channels including call centers, brand and third-party Web sites, and dealer networks. You will be able to track data regarding customers, vehicles, partners, dealer rela-tionships, and business transactions. You can use rules-based lead distribution to get the right leads to the right dealers. And you can leverage data in collaborative marketing activities such as strategic brand management, sales and service campaigns, customer loyalty programs, satisfaction surveys, commercial advertising, and event management activities such as vehicle transportation and disposition.With digital asset management tools, all of your digital content and rich media files – such as brochures and flyers – will be avail-able in a central repository. You’ll also be able to track marketing expenses using scenario planning and financial forecasting tools that allow you to generate detailed cost plans and simulate the effects of financial accruals.Closing the Loop on the Customer Interaction Cycle The quality and convenience of services are key factors in auto-motive customers’ choice of brand or dealership. To properly serve customers and grow brand loyalty, you need to be able to deliver consistent communication and reliable service offers synchronously across multiple channels. This illustrates a sig-nificant challenge faced by OEMs – the potential disconnect between the manufacturer and the end customer. Incomplete information often leads to redundant or even conflicting messages being sent to the consumer. As a result, OEMs and importers, as well as dealers, need access to complete and reliable customer and vehicle information to deliver efficient customer service. The mySAP CRM solution provides a customer interaction center – tailored for the automotive industry – that gives you accessto the information you need to implement case handling, mar-keting campaigns, satisfaction surveys, complaints, appraisals, service requests, call backs, and accessory sales. Users can search and display all customer and vehicle data and manage business transactions. The interaction center supports you in all your contacts with customers and dealers, across multiple brands and channels, assuring consistent and reliable communication with your customers and a rewarding customer experience during every interaction – be it on the phone, in person, via e-mail, or on the Web. The result: you can manage and track complaints to ensure proper resolution and provide higher quality customer service around the clock.Your managers can also oversee and track relevant customer service information more efficiently with the mySAP CRMinteraction center. With an easy-to-use dashboard and improved real-time monitoring applications, managers can track call list status, call response and processing times, e-mail response status and more. User-friendly tools help you model interaction center processes and scripts, and share information with center agents.Where appropriate, the solution’s dealer collaboration tools let you share information and involve dealer personnel directly in issue resolution.For additional efficiencies, a rules-based e-mail response manage-ment system allows you to automatically route e-mail, prepare responses, create interaction records and service tickets, and link to existing tickets. The solution brings more visibility to the process as well, with tools for reporting and analytics.And with case management tools you can link customer and vehicle data to search for customer-initiated communications –including requests for product details and brochures, or com-plaints about service. Survey tools allow you to capture customer input and perform analysis on collected data, helping you to close the loop on the customer interaction cycle. Metric and anecdotal information collected through the interaction center is also a key component of early warning systems that keep you abreast of shifts in preferences, customer requirements, and economic conditions. /contactsap50 058 951 (05/08)©2005 by SAP AG. All rights reserved. SAP , R/3, mySAP , mySAP .com, xApps, xApp, SAP NetWeaver, and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world. All other product and service names mentioned are the trademarks of their respective companies. Data contained in this document serves informational purposes only. National product specifications may vary. Printed on environmentally friendly paper.These materials are subject to change without notice. These materials are provided by SAP AG and its affiliated companies (“SAP Group”)for informational purposes only, without representation or warranty of any kind, and SAP Group shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP Group products and services are those that are set forth in the express warranty state-ments accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty.Increase Revenues and Cut Costs Across the Value ChainWith its industry-specific capabilities and comprehensive support for industry processes, mySAP CRM helps you increase flexibility,speed, efficiency, and profitability across the sales and service value chain. With specific configurations tailored to the needs of the automotive industry, mySAP CRM is the proven solution to support end-to-end marketing, sales, and service processes.You can expect the following solid business benefits:•Increased efficiency and reduced costs.To help stream-line communications and reduce friction between dealer and brand operations, OEMs and dealers can collaborate on eliminating customer-facing and back-office inefficiencies involving manual and redundant processes.•Improved brand and customer ing enhanced access to customer information across channels and access points, you can improve your understanding of individual customer relationships. You can use improved monitoring and targeting tools to execute more effective marketing campaigns. And the analytical capabilities will provide greater information transparency to better under-stand the overall profitability of individual customers.•Better channel management.The SAP solution allows you to collaborate seamlessly, from OEM to the dealer point of sale. In addition, you can increase sales force efficiency,productivity, and close rates by being better able to manage and qualify leads and contacts. The solution’s capabilities for configuring, ordering, and customer assignment also let you increase sales and improve vehicle service.Find Out How SAP Can Help Drive Your SuccessTo find out more about how SAP can help you with a complete solution for your customer-centric business call your SAP representative today or visit us online at /industries/automotive .。
BW介绍
Buy
Make
Collaborative Manufacturing
Sell
Move
Execution
Collaborative Procurement
Collaborative Fulfillment
SAP AG 2002, Title of Presentation, Speaker Name 4
Best Practices Reduce Your Time to Value
Quick and easy way for new and existing customers to implement mySAP SCM
Dev.
Prices for mySAP SCM
Presentation Clients Middleware
Non - R/3 Core R/3 Core
Web Browser ITS : WGate and AGate with Workplace liveCache Optimizer
CRM BW APO HR
FI
CO..
SAP Basis
BW Webserver ITS
Presentation Client
APO
App. Server
APOApplication
BW-Layer
Optimizer
OLTP R/3
OLTP R/3
Database
Database Server
APO-DB
APOApplication
Database
liveCache
Networking
Private Exchanges, Portals, Mobile Bus. Networking
ho问题回答
HO1. IntroductionHO, short for Handover, is a fundamental concept in wireless communication systems. It refers to the process of transferring an ongoing call or data session from one cell to another without interrupting the communication. Handovers are crucial in maintaining seamless connectivity and ensuring smooth user experience in mobile networks.In this article, we will explore the significance of handovers, understand the various types of handovers used in different scenarios, and delve into the technical aspects of handover procedures.2. Significance of HandoversHandovers play a vital role in mobile communication systems for several reasons:2.1 Seamless ConnectivityOne of the primary objectives of handovers is to ensure uninterrupted connectivity for mobile users. As users move from one cell to another while making calls or using data services, it is essential to transfer their ongoing sessions seamlessly without any disruptions. Handovers enable this smooth transition between cells, allowing users to maintain their connections without experiencing call drops or data loss.2.2 Load BalancingHandovers also facilitate load balancing in cellular networks. By intelligently distributing users across multiple cells, handover mechanisms help optimize network resources and prevent congestion in specific cells. This dynamic load management ensures efficientutilization of network capacity and enhances overall network performance.2.3 Quality of Service (QoS)Handovers contribute significantly to maintaining QoS parameters such as call quality and data throughput. When a user moves towards the edge of a cell’s coverage area, signal strength may weaken, leading to degradedservice quality. By triggering a handover to a neighboring cell with better signal strength, QoS can be maintained at an acceptable level.3. Types of HandoversThere are several types of handovers used in different scenarios based on network architectures and mobility patterns:3.1 Intra-Cell HandoverIntra-cell handover, also known as soft handover, occurs when a mobile device moves within the coverage area of a single base station. In this case, the handover process involves transferring the connection between different sectors or antennas within the same cell. Intra-cell handovers are typically transparent to users and ensure seamless connectivity without noticeable disruptions.3.2 Inter-Cell HandoverInter-cell handover, also referred to as hard handover, takes place when a mobile device moves from one cell to another within the same network. This type of handover involves transferring the ongoing session from the serving cell to a target cell. Inter-cell handovers require coordination between multiple base stations and involve more complex procedures compared to intra-cell handovers.3.3 Inter-System HandoverInter-system handover occurs when a mobile device moves betweendifferent wireless technologies or networks, such as from GSM (2G) to UMTS (3G) or from LTE (4G) to Wi-Fi. These handovers involve not only changing cells but also transitioning between different network architectures and protocols.3.4 Vertical HandoverVertical handovers are specific types of inter-system handovers that involve switching between heterogeneous networks with varying characteristics. For example, a vertical handover may occur when a user transitions from cellular network coverage to Wi-Fi connectivity or vice versa. These handovers aim to provide seamless connectivity while considering factors such as signal strength, network availability, and user preferences.4. Handover ProceduresHandovers involve several steps and procedures that ensure successful transfer of ongoing sessions:4.1 Measurement and TriggeringThe first step in a handover procedure is measuring the signal quality and strength of neighboring cells or systems. The serving cell continuously monitors these measurements and triggers a handover decision when certain predefined thresholds are met.4.2 Handover DecisionOnce triggered, the handover decision is made based on various factors such as signal strength, interference levels, network load, and QoS requirements. The decision-making process aims to select the most suitable target cell or system for handover.4.3 Handover PreparationAfter the handover decision, the serving cell initiates preparations for the handover. This involves allocating resources in the target cell and coordinating with neighboring base stations or systems.4.4 Handover ExecutionDuring the handover execution phase, the mobile device switches its connection from the serving cell to the target cell. The switch should be seamless and imperceptible to users, ensuring uninterrupted communication.4.5 Handover CompletionOnce the handover is executed successfully, a confirmation message is exchanged between base stations or systems to finalize the handover process. This ensures that both ends of the communication are aware of the transition and can resume normal operation.5. ConclusionHO (Handover) is an essential mechanism in wireless communication systems that enables seamless connectivity, load balancing, and maintenance of quality of service parameters. By understanding different types of handovers and their procedures, network operators can optimizetheir networks for efficient resource utilization and improved user experience.Handovers continue to evolve with advancements in technology, such as 5G networks and network slicing. These developments aim to further enhance handover capabilities and provide even better connectivity in future wireless communication systems.Remember: HO is not just a simple abbreviation; it represents a critical aspect of mobile networks that keeps us connected wherever we go!。
可重构智能表面辅助的通信感知一体化系统
可重构智能表面辅助的通信感知一体化系统作者：杨晓宇尉志青孟春伟来源：《中兴通讯技术》2022年第05期摘要：通信感知一体化（ISAC）是6G移动通信的候选技术之一，可实现感知和通信的集成和优势互补。
可重构智能表面（RIS）能够智能地控制传播环境，提高网络的容量和覆盖率，已成为6G实现广泛连接的一项关键技术。
认为将RIS部署于ISAC系统可以提供一个新的通信和感知性能优化维度。
从ISAC的研究意义出发，探讨ISAC的关键技术，概述RIS的工作原理及其在感知系统和通信系统中的应用，并重点分析RIS辅助ISAC以更好地实现感知目标和服务通信用户的研究现状。
关键词：ISAC；可重构智能表面；6G；频谱资源Abstract： Integrated sensing and communication （ISAC） is recognized as one of the candidate technologies of 6G mobile communication， aim？ ing to realize the integration and mutual benefit of sensing and communication. Considering that the reconfigurable intelligent surface （RIS） can intelligently control the propagation environment to improve the capacity and coverage of the network， it has become a key technology for 6G to achieve extensive connectivity. It isbelieved that deploying RIS on ISAC systems can provide a new performance optimization di？mension of communication and sensing. The research significance of ISAC is highlighted， and the key technologies of ISAC are discussed. The working principles of RIS and its applications in sensing system and communication systems are summarized. Finally， the research sta？ tus of RIS-assisted ISAC to better realize the sensing target and serve the communication users is analyzed.Keywords： ISAC； RIS； 6G； spectrum resource目前，6G移動通信被设想为一个集成感知、通信和计算等功能的系统，并朝着高数据速率和智能化的方向发展[1]。
Topology Control in Heterogeneous Wireless
Topology Control in Heterogeneous Wireless Networks:Problems and SolutionsNing Li and Jennifer C.HouDepartment of Computer ScienceUniversity of Illinois at Urbana-ChampaignUrbana,IL61801{nli,jhou}@Abstract—Previous work on topology control usually assumes homogeneous wireless nodes with uniform transmission ranges. In this paper,we propose two localized topology control algo-rithms for heterogeneous wireless multi-hop networks with non-uniform transmission ranges:Directed Relative Neighborhood Graph(DRNG)and Directed Local Spanning Subgraph(DLSS). In both algorithms,each node selects a set of neighbors based on the locally collected information.We prove that(1)the topologies derived under DRNG and DLSS preserve the network connectivity;(2)the out degree of any node in the resulting topology by DLSS is bounded,while the out degree cannot be bounded in DRNG;and(3)the topologies generated by DRNG and DLSS preserve the network bi-directionality.I.I NTRODUCTIONEnergy efficiency[1]and network capacity are perhaps two of the most important issues in wireless ad hoc networks and sensor networks.Topology control algorithms have been proposed to maintain network connectivity while reducing energy consumption and improving network capacity.The key idea to topology control is that,instead of transmitting using the maximal power,nodes in a wireless multi-hop network collaboratively determine their transmission power and define the network topology by forming the proper neighbor relation under certain criteria.By enabling wireless nodes to use adequate transmission power(which is usually much smaller than the maximal trans-mission power),topology control can not only save energy and prolong network lifetime,but also improve spatial reuse(and hence the network capacity)[2]and mitigate the MAC-level medium contention[3].Several topology control algorithms [3]–[10]have been proposed to create power-efficient network topology in wireless multi-hop networks with limited mobility (a summary is given in Section III).However,most of them as-sume homogeneous wireless nodes with uniform transmission ranges(except[4]).The assumption of homogeneous nodes does not always hold in practice,since even devices of the same type may have slightly different maximal transmission power.There also exist heterogeneous wireless networks in which devices have dramatically different capabilities,for instance,the communi-cation network in the Future Combat System which involves wireless devices on soldiers,vehicles and UA Vs.As will be exemplified in Section III,most existing algorithms cannot be directly applied to heterogeneous wireless multi-hop networks in which the transmission range of each node may be different. To the best of our knowledge,this paper is thefirst effort to address the connectivity and bi-directionality issue in the heterogeneous wireless networks.In this paper,we propose two localized topology control al-gorithms for heterogeneous wireless multi-hop networks with non-uniform transmission ranges:Directed Relative Neighbor-hood Graph(DRNG)and Directed Local Spanning Subgraph (DLSS).In both algorithms,the topology is constructed by having each node build its neighbor set and adjust its trans-mission power based on the locally collected information. We are able to prove that(1)the topology derived under both DRNG and DLSS preserves network connectivity,i.e., if the original topology generated by having every node use its maximal transmission power is strongly connected,then the topologies generated by both DRNG and DLSS are also strongly connected;(2)the out degree of any node in the topology by DLSS is bounded,while the out degree of nodes in the topology by DRNG may be unbounded;and(3)the topology generated by DRNG and DLSS preserves network bi-directionality,i.e.,if the original topology by having every node use its maximal transmission power is bi-directional,then the topology generated by either DRNG or DLSS is also bi-directional after some simple operations.Simulation results indicate that,compared with the other known topology control algorithms that can be applied to het-erogeneous networks,DRNG and DLSS have smaller average node degree(both logical and physical)and smaller average link length.The former reduces the MAC-level contention, while the latter implies a small transmission power needed to maintain connectivity.The rest of the paper is organized as follows.In Section II, we give the network model.In Section III,we summarize previous work on topology control,and give examples to show why existing algorithms cannot be directly applied to heterogeneous networks.Following that,we present both the DRNG and DLSS algorithms in Section IV,and prove several of their useful properties in Section V.Finally,we evaluate the performance of the proposed algorithms in Section VI, and conclude the paper in Section VII.使用DRNG和DLSS进行拓扑控制丗连通性和双向性II.N ETWORK M ODELConsider a set of nodes(vertices),V={v1,v2,...,v n}, which are randomly distributed in the2-D plane.Assume the area that a transmission can cover is a disk.We define the range of a node v i as the radius of the disk that v ican cover using its maximal transmission power,denoted r vi .In a heterogeneous network,the transmission ranges of all nodes may not be the same.Let r min=min v∈V{r v}and r max=max v∈V{r v}.We denote the network topology generated by having each node use its own maximal transmission power as a simple directed graph G=(V(G),E(G)),where E(G)={(u,v): d(u,v)≤r u,u,v∈V(G)}is the edge(link)set of G,and d(u,v)is the Euclidean distance between node u and node v.Note that(u,v)is an ordered pair representing an edge from node u to node v,i.e.,(u,v)and(v,u)are two different edges.A unique id(such as an IP/MAC address)is assigned to each node.Here we let id(v i)=i for simplicity.We assume that the wireless channel is symmetric and obstacle-free,and each node is equipped with the capability to gather its location information via,for example,GPS for outdoor applications and pseudolite[11]for indoor applica-tions,and many other lightweight localization techniques for wireless networks(see[12]for a summary).Before delving into the technical discussion and algorithm description,we give the definition of several terms that will be used throughout the paper.Definition1(Reachable Neighborhood):The reachable neighborhood N R u is the set of nodes that node u can reach using its maximal transmission power,i.e., N R u={v∈V(G):d(u,v)≤r u}.For each node u∈V(G), let G R u=(V(G R u),E(G R u))be an induced subgraph of G such that V(G R u)=N R u.Definition2(Weight Function):Given two edges (u1,v1),(u2,v2)∈E and the Euclidean distance function d(·,·),weight function w:E→R satisfies:w(u1,v1)>w(u2,v2)⇔d(u1,v1)>d(u2,v2)or(d(u1,v1)=d(u2,v2)&&max{id(u1),id(v1)}>max{id(u2),id(v2)}) or(d(u1,v1)=d(u2,v2)&&max{id(u1),id(v1)}=max{id(u2),id(v2)}&&min{id(u1),id(v1)}>min{id(u2),id(v2)}). This weight function ensures that two edges with different end-vertices have different weights.Note,however,that w(u,v)= w(v,u).Definition3(Neighbor Set):Node v is a neighbor of node u under an algorithm A,denoted u A−→v,if and only if there exists an edge(u,v)in the topology generated by the algorithm.In particular,we use u→v to denote the neighbor relation in G.u A←→v if and only if u A−→v and v A−→u.The Neighbor Set of node u is N A(u)={v∈V(G):u A−→v}.Definition4(Topology):The topology generated by an al-gorithm A is a directed graph G A=(E(G A),V(G A)),where V(G A)=V(G),E(G A)={(u,v)∈E(G):u A−→}.Definition5(Radius):The radius,R u,of node u is defined as the distance between node u and its farthest neighbor(in terms of Euclidean distance),i.e,R u=max v∈NA(u){d(u,v)}. Definition6(Connectivity):For any topology generated by an algorithm A,node u is said to be connected to node v(denoted u⇒v)if there exists a path(p0= u,p1,...,p m−1,p m=v)such that p i A−→p i+1,i= 0,1,...,m−1,where p k∈V(G A),k=0,1,...,m.It follows that u⇒v if u⇒p and p⇒v for some p∈V(G A). Definition7(Bi-Directionality):A topology generated by an algorithm A is bi-directional,if for any two nodes u,v∈V(G A),u∈N A(v)implies v∈N A(u).In other words,the topology generated by A is bi-directional if all edges in the topology are bi-directional.Definition8(Bi-Directional Connectivity):For any topol-ogy generated by an algorithm A,node u is said to be bi-directionally connected to node v(denoted u⇔v)if there exists a path(p0=u,p1,...,p m−1,p m=v)such that p i A←→p i+1,i=0,1,...,m−1,where p k∈V(G A),k= 0,1,...,m.It follows that u⇔v if u⇔p and p⇔v for some p∈V(G A).Deriving network topology consisting of only bi-directional links facilitates link level acknowledgment,which is a critical operation for packet transmissions and retransmissions over unreliable wireless media.Bi-directionality is also important in floor acquisition mechanisms such as the RTS/CTS mechanism in IEEE802.11.Definition9(Addition and Removal):The operation Addi-tion is to add an extra edge(v,u)into G A if(u,v)∈E(G A), (v,u)/∈E(G A),and d(u,v)≤r v.The operation Removal is to delete any edge(u,v)∈E(G A)if(v,u)/∈E(G A).Let G+Aand G−Adenote the resulting topologies after applying Addition and Removal to G A,respectively.Both the Addition and Removal operations attempt to create a bi-directional topology by removing uni-directional edges or converting uni-directional edges into bi-directional.The result-ing topology after Removal is alway bi-directional,although it may not be strongly connected.The resulting topology after Addition is not necessarily bi-directional,as it essentially tries to increases the transmission power of a node v to a level that may be beyond its capability.III.R ELATED W ORK AND W HY T HEY C ANNOT BED IRECTLY A PPLIED TO H ETEROGENEOUS N ETWORKS Several topology control algorithms[3]–[10]have been proposed.In this section,wefirst summarize these algorithm and then give examples on why they cannot be directly applied to heterogeneous networks.A.Related WorkRodoplu et al.[4](denoted R&M)introduced the notion of relay region and enclosure for the purpose of power control.Instead of transmitting directly,a node chooses tobe defined in SectionIII-B).be defined in Section IV).Fig.1.The definition of the Directed Relative Neighborhood Graph. relay through other nodes if less power will be consumed.It is shown in the paper that the network is strongly connected if every node maintains links with the nodes in its enclosure and the resulting topology is a minimum power topology. The major drawback is that it requires an explicit propagation channel model to compute the relay region(in the simulation study presented in Section VI,we assume that the free-space model is used),hence the resulting topology is sensitive to the model used in the computation.Also,it assumes there is only one data sink(destination)in the network.Ramanathan et al.[5]presented two centralized algorithms to minimize the maximal power used per node while maintain-ing the(bi)connectivity of the network.They introduced two distributed heuristics for mobile networks.Both centralized algorithms require global information,and thus cannot be directly deployed in the case of mobility.On the other hand, the proposed heuristics cannot guarantee the preservation of the network connectivity.COMPOW[3]and CLUSTERPOW[7]are approaches im-plemented in the network layer.Both hinge on the idea that if each node uses the smallest common power required to main-tain network connectivity,the traffic carrying capacity of the entire network is maximized,the battery life is extended,and the MAC-level contention is mitigated.The major drawback is its significant message overhead,since each node has to run multiple daemons,each of which has to exchange link state information with their counterparts at other nodes.CBTC(α)[6]is a two-phase algorithm in which each node finds the minimum power p such that some node can be reached in every cone of degreeα.The algorithm has been proved to preserve network connectivity ifα<5π/6.Several optimization methods(that are applied after the topology is derived under the base algorithm)are also discussed to further reduce the transmitting power.To facilitate the following discussion,the definition of the Relative Neighborhood Graph(RNG)is given below.Definition10(Neighbor Relation in RNG):For RNG[13], [14],u RNG←−−→v if and only if there does not exist a third node p such that w(u,p)<w(u,v)and w(p,v)<w(u,v). Or equivalently,there is no node inside the shaded area in Fig.1(a).Borbash and Jennings[8]proposed to use RNG for the topology initialization of wireless networks.Based on the local knowledge,each node makes decisions to derive the network topology based on RNG.The network topology thus derived has been reported to exhibit good overall performance in terms of power usage,low interference,and reliability.Li et al.[9]presented the Localized Delaunay Triangula-tiona,a localized protocol that constructs a planar spanner of the Unit Disk Graph(UDG).The topology contains all edges that are both in the unit-disk graph and the Delaunay triangulation of all nodes.It is proved that the shortest path in this topology between any two nodes u and v is at most a constant factor of the shortest path connecting u and v in UDG. However,the notion of UDG and Delaunay triangulation cannot be directly extended to heterogeneous networks.In[10],we proposed LMST(Local Minimum Spanning Tree)for topology control in homogeneous wireless multi-hop networks.In this algorithm,each node builds its local minimum spanning tree independently and only keeps on-tree nodes that are one-hop away as its neighbors in the final topology.It is proved that(1)the topology derived under LMST preserves the network connectivity;(2)the node degree of any node in the resulting topology is bounded by 6;and(3)the topology can be transformed into one with bi-directional links(without impairing the network connectivity) after removal of all uni-directional links.Simulation results show that LMST can increase the network capacity as well as reduce the energy consumption.Instead of adjusting the transmission power of individual devices,there also exist other approaches to generate power-efficient topology.By following a probabilistic approach,Santi et al.derived the suitable common transmission range which preserves network connectivity,and established the lower and upper bounds on the probability of connectedness[15].In[16], a“backbone protocol”is proposed to manage large wireless ad hoc networks,in which a small subset of nodes is selected to construct the backbone.In[17],a method of calculating the power-aware connected dominating sets was proposed totrol)is strongly connected.23mization is not strongly connected:there is no path from v 1to v 3.Fig.2.An example that shows CBT C (23π)may render disconnectivity in heterogeneous networks.There is no path from v 1to v 3due to the loss of edge (v 2,v 3),which is discarded by v 2since v 1and v 4have already provided the necessarycoverage.trol)is stronglyconnected.nected:there is no path from v 5to v 2.Fig.3.An example that shows RNG may render disconnectivity in heterogeneous networks.There is no path from v 5to v 2due to the loss of edge (v 4,v 2),which is discarded since |(v 4,v 5)|<|(v 4,v 2)|,and |(v 2,v 5)|<|(v 4,v 2)|.trol)is stronglyconnected.nected:there is no path from v 3to v 5.Fig.4.An example that shows MRNG may render disconnectivity in heterogeneous networks.There is no path from v 3to v 5due to the loss of edge (v 2,v 5),which is discarded since |(v 2,v 3)|<|(v 2,v 5)|,and |(v 5,v 3)|<|(v 2,v 5)|.topology control)is stronglyconnected.at v 8.at v 7.strongly connected:there is no path from v 7to v 4.Fig.5.An example that shows the algorithm in which each node builds a local directed minimum spanning tree and only keeps the one-hop neighbors may result in disconnectivity.establish an underlying topology for the network.B.Why Existing Algorithms Cannot be Directly Applied to Heterogeneous NetworksMost existing topology control algorithms(except[4])as-sume homogeneous wireless nodes with uniform transmission ranges.When directly applied to heterogeneous networks, these algorithms may render disconnectivity.In this subsec-tion,we give several examples to motivate the need for new topology control algorithms for heterogeneous networks.As shown in Fig.2(a)-(b)(note that in Figs.2–5we use arrows to indicate the direction of the links to represent a linkfrom u to v),the network topology derived under CBT C(23π)(without optimization)may not preserver the connectivity, when the algorithm is directly applied to a heterogeneousnetwork.CBT C(56π)also has the same problem.Similarly we show in Fig.3(a)-(b)that the network topology derived under RNG may be disconnected when the algorithm is directly applied to a heterogeneous network.As RNG is defined for undirected graphs,one may tailor the definition of RNG for directed graphs.Definition11(Neighbor Relation in MRNG):For Modified Relative Neighborhood Graph(MRNG),u MRNG−−−−−→v if and only if there does not exist a third node p such that w(u,p)< w(u,v),d(u,p)≤r u and w(p,v)<w(u,v),d(v,p)≤r v (Fig.1(b)).As shown in Fig.4(a)-(b),the topology derived under MRNG may still be disconnected(we will give another variation of RNG for directed graphs in the next section). One possible extension of LMST[10]is for each node to build a local directed minimum spanning tree[18]–[20] and keep only neighbors within one hop.Unfortunately,the resulting topology does not preserve the strong connectivity, as shown in Fig.5.In the next section,we will improve on this approach to preserve the connectivity.IV.DRNG AND DLSSIn this section,we propose two localized topology con-trol algorithms for heterogeneous wireless multi-hop net-works with non-uniform transmission ranges:Directed Rela-tive Neighborhood Graph(DRNG)and Directed Local Span-ning Subgraph(DLSS).In both algorithms,the topology is derived by having each node build its neighbor set and adjust its transmission power based on locally collected information. Several nice properties of both algorithms will be discussed in Section V.Both algorithms are composed of three phases:1)Information Collection:each node collects the localinformation of neighbors such as position and id,and identifies the Reachable Neighborhood N R.2)Topology Construction:each node defines(in compli-ance with the algorithm)the proper list of neighbors for thefinal topology using the information in N R.3)Construction of Topology with Only Bi-Directional Links(Optional):each node adjusts its list of neighbors to make sure that all the edges are rmation collectionThe information needed by each node u for topology control is the information of its reachable neighborhood N R.This can be obtained locally,in the case of homogeneous networks, by having each node broadcast periodically a Hello message using its maximal transmission power.The information con-tained in a Hello message should at least include the node id and the position of the node.These periodic messages can be sent either in the data channel or in a separate control channel. In heterogeneous networks,having each node broadcast a Hello message using its maximal transmission power may be insufficient.For example,as shown in Fig.6,v1is unable to know the position of v4since v4cannot reach v1.We will treat this issue rigorously in Section V-D.For the time being, we assume that by the end of thefirst phase every node u obtains its N R u.Fig.6.An example that shows having each node broadcast a Hello message using its maximal transmission power may be insufficient for some nodes (e.g.,node v1)to know their reachable neighborhood.Thisfigure also serves to show that given an arbitrary direct graph,it may be impossible to derive a bi-directional topology.B.Topology constructionFirst we define the neighbor relation used in both algo-rithms.Definition12(Neighbor Relation in DRNG):For Directed Relative Neighborhood Graph(DRNG),u DRNG−−−−−→v if and only if d(u,v)≤r u and there does not exist a third node p such that w(u,p)<w(u,v)and w(p,v)<w(u,v),d(p,v)≤r p(see Fig.1(c)).Definition13(Neighbor Relation in DLSS):For Directed Local Spanning SubGraph(DLSS),u DLSS−−−−→v if and only if (u,v)∈E(T u),where T u is obtained by applying Algorithm1 to G R u.T u is a directed local spanning subgraph that spans N R u.Hence node v is a neighbor of node u if and only if node v is on node u’s directed local MST T u,and is one-hop away from node u.DLSS is a natural extension of LMST[10]for hetero-geneous networks.Instead of computing a directed local MST(which minimizes the total cost of the all edges in the subgraph,and is shown to be wrong in Section III-B),Algorithm1DLSS(u)INPUT:G R u,the induced subgraph of G that spans the reachable neighborhood of u;OUTPUT:T u=(V Tu ,E Tu),a local spanning subgraph ofG R u;1:V T u:=V,E T u:=∅;2:sort all edges in E(G R u)in the ascending order of weight (as defined in Definition2);3:for each edge(u,v)in the order do4:if u is not connected to v in T u then5:E T u:=E T u∪{(u,v)};6:end if7:if u is connected to all nodes in N R u then8:exit;9:end if10:end foreach node u computes a directed local subgraph according to Algorithm1(which minimizes the maximum cost of all edges in the subgraph)and takes on-tree nodes that are one-hop away as its neighbors.Each node can broadcast its own maximal transmission power in the Hello message.By measuring the receiving power of Hello messages,each node u can determine the specific power level required to reach each of its neighbors [10].Node u then uses the power level that can reach its farthest neighbor as its transmission power.This approach can be applied without knowing the actual propagation model. C.Construction of topology with only bi-directional edges As illustrated in the previous section,some links in G DLSS may be uni-directional.There also exist uni-directional links in G DRNG.We can apply either Addition or Removal to G DLSS and G DRNG to obtain bi-directional topologies.We will discuss some properties of these solutions in Section V-B.V.P ROPERTIES OF DRNG AND DLSSIn this section,we discuss the connectivity,bi-directionality and degree bound of DLSS and DRNG.We always assume G is strongly connected,i.e.,u⇒v in G for any u,v∈V(G).A.ConnectivityLemma1:For any edge(u,v)∈E(G),we have u⇒v in G DLSS.Proof:Let all the edges(u,v)∈E(G)be sorted in the increasing order of weight,i.e.,w(u1,v1)<w(u2,v2)< ...<w(u l,v l),where l is the total number.We prove by induction.1)Basis:Thefirst edge(u1,v1)satisfies w(u1,v1)=min(u,v)∈E(G){w(u,v)}.According to Algorithm1, (u1,v1)and(v1,u1)will be inserted into G DLSS,i.e., u1DLSS←−−→v1.2)Induction:Assume the hypothesis holds for all edges(u i,v i),1≤i<k,we prove u k⇒v k in G DLSS.If u k DLSS−−−−→v k,then u k⇒v k.Otherwise in the localtopology construction of u,before edge(u k,v k)was inserted into T uk,there must already exist a path p= (w0=u k,w1,w2,···,w m−1,w m=v k)from u k to v k, where(w i,w i+1)∈E(T uk),i=0,1,···,m−1.Since edges are inserted in a ascending order of weight,we have w(w i,w i+1)<w(u k,v k).Applying the induction hypothesis to each pair[w i,w i+1],i=0,1,···,m−1, we have w i⇒w i+1,thus u k⇒v k.Theorem1:G DLSS preserves the connectivity of G,i.e., G DLSS is strongly connected if G is strongly connected.Proof:Suppose G is strongly connected.For any two nodes u,v∈V(G),there exists at least one path p= (w0=u,w1,w2,···,w m−1,w m=v)from u to v,where (w i,w i+1)∈E(G),i=0,1,···,m−1.Since w i⇒w i+1 by Lemma1,we have u⇒v.Lemma2:Given three nodes u,v,w∈V(G DLSS)satisfy-ing w(u,v)>w(u,w)and w(u,v)>w(w,v),d(w,v)≤r w, then u v in G DLSS.Proof:We only need to consider the case where d(u,v)≤r u since d(u,v)>r u would imply u v.Consider the local topology construction of u.Before we insert(u,v) into T u,the two edges(u,p)and(p,v)have already been processed since w(u,p)<w(u,v)and w(p,v)<w(u,v). Thus u⇒p and p⇒v,which means u⇒v.Therefore, (u,v)should not be inserted into T u according to Algorithm1, i.e.,u v in G DLSS.Theorem2:The edge set of G DLSS is a subset of the edge set of G DRNG,i.e.,E(G DLSS)⊆E(G DRNG).Proof:We prove by contradiction.Given any edge (u,v)∈E(G DLSS),assume(u,v)/∈E(G DRNG).According to the definition of DRNG,there must exist a third node p such that w(u,p)<w(u,v),d(u,p)≤r u and w(p,v)< w(u,v),d(p,v)≤r p.By Lemma2,u v in G DLSS,i.e., (u,v)/∈E(G DLSS).Theorem3(Connectivity of DRNG):If G is strongly con-nected,then G DRNG is also strongly connected.Proof:This is a direct result of Theorem1and Theo-rem2.B.Bi-directionalityNow we discuss the bi-directionality property of DLSS and DRNG.Since Addition may not always result in bi-directional topologies,wefirst apply Removal to topologies by DLSS and DRNG.It turns out the simple Removal operation may lead to disconnectivity.Examples are given in Figs.7–8to show, respectively,that DLSS and DRNG with Removal may result in disconnectivity.In general,G may not be bi-directional if the transmission ranges are non-uniform.Since the maximal transmission range can not be increased,it may be impossible tofind a bi-directional connected subgraph of G for some cases.Antrol)is strongly connected.strongly connected:there are 2components.Fig.7.An example that shows DLSS with Removal may result indisconnectivity.trol)is stronglyconnected.nected.strongly connected:there are 2components.Fig.8.An example that shows DRNG with Removal may result in disconnectivity.example is given in Fig.6:v 1can reach v 2and v 4,v 2can reach v 1and v 3,v 3can reach v 2and v 4,and v 4can reach v 2only.Addition does not lead to bi-directionality since all edges entering or leaving v 4are uni-directional with all nodes already transmitting with their maximal power.On the other hand,Removal will partition the network.In this example,although the graph G is strongly connected,its subgraph with the same vertex set cannot be both connected and bi-directional.Now we show that bi-directionality can be ensured if the original topology is both strongly connected and bi-directional.Theorem 4:If the original topology G is strongly connected and bi-directional,then G DLSS and G DRNG are also strongly connected and bi-directional after Addition or Removal .Proof:Since E (G DLSS )⊆E (G DRNG ),we have E (G −DLSS )⊆E (G +DLSS )and E (G −DLSS )⊆E (G −DRNG )⊆E (G +DRNG ).Therefore,we only need to prove that G −DLSS preserves the strong connectivity.In the Induction step in Lemma 1,the only reason wecannot prove that u k DLSS←−−→v k is that edge (v k ,u k )may not exist.Given that G is bi-directional,we are able to provethat u k DLSS←−−→v k .Hence for any edge (u,v )∈E (G ),we have u ⇔v in G DLSS .The removal of asymmetric edges in G DLSS does not affect this property.Therefore,G −DLSS is still stronglyconnected.uFig.9.The definition of Cone (u,α,v ).C.Degree BoundIt has been observed that any minimum spanning tree of a simple undirected graph in the plane has a maximum node degree of 6[21].However,this bound does not hold for directed graphs.An example is shown in Fig.10,where node u has 18neighbors.In this section,we will discuss the node degree in the topology by DLSS and DRNG.Definition 14(Disk):Disk (u,r )is the disk centered at node u with a radius of r .Definition 15(Cone):Cone (u,α,v )is the unbounded shaded region shown in Fig.9.The following corollary is a direct result of Lemma 1.Corollary 1:If v is a neighbor of u ’s in G DLSS ,and d (u,v )≥r min ,then u can not have any other neighbor inside Disk (v,r min ).Theorem 5:For any node u ∈V (G DLSS ),the number of。
异质车联网环境下耦合映射跟驰模型的协同控制问题
关键词: 异质车联网; 耦合映射跟驰模型; 滞后反应时间; 协同控制; 稳定性 引用格式: 翟聪, 巫威眺, 黄玲. 异质车联网环境下耦合映射跟驰模型的协同控制问题. 控制理论与应用, 2019, 36(1): 96 – 107 DOI: 10.7641/CTA.2018.70431
Collaborative control of coupled map car-following model under
heterogeneous connected vehicle environment
ZHAI Cong1,2, WU Wei-tiao2†, HUANG Ling2
(1. School of Civil Engineering and Transportation, Foshan University, Foshan Guangdong 528000, China; 2. School of Civil Engineering and Transportation, South China University of Technology, Guangzhou Guangdong 510640, China) Abstract: In this paper, we propose a more realistic coupled map car following model considering the driver’s characteristics of the delay changing over time. Using the theory of Lyapunov function, the sufficient conditions for system stability of the model is presented. Thereafter, we design a new state feedback controller taking into account vehicles sensors failures, which drives the closed-loop system to asymptotic stability in the provision of partial vehicles sensor failure, such that the congestion problem can be effectively suppressed. The gain parameters of the controller are attained by MATLAB’s LMIs toolbox. In the numerical example, the performance of designed controller is compared to those of the conventional Konishi controller and without any control. The impact of percentage and location of vehicles on the performance of the controller is also analyzed, which verifies the effectiveness of our method. Key words: heterogeneous connected vehicle; coupled-map car following model; time delay; collaborative control; stability Citation: ZHAI Cong, WU Weitiao, HUANG Ling. Collaborative control of coupled map car-following model under heterogeneous connected vehicle environment. Control Theory & Applications, 2019, 36(1): 96 – 107
heterogeneous element -回复
heterogeneous element -回复Heterogeneous Element: A Journey Through Diversity and UnityIntroduction:In a world filled with diverse cultures, belief systems, and perspectives, the concept of a heterogeneous element has become a vital aspect of our society. A heterogeneous element refers to any entity that displays a combination of different elements, whether it be people, objects, or ideas. This article aims to explore the significance and impact of such elements, focusing on their manifestation in various realms of human life and highlighting the ways in which they contribute to the unity of our global community.1. Defining Heterogeneous Elements:To begin, let us delve into the definition of a heterogeneous element. Put simply, it is an entity that possesses different characteristics or qualities within itself. These elements can be found in a wide range of contexts, such as biodiversity, cultural diversity, or even technological advancements. The beauty of these elements lies in their unique ability to blend different componentstogether, offering new perspectives and possibilities.2. Heterogeneous Elements in Nature:One of the most striking manifestations of heterogeneous elements can be observed in nature through biodiversity. From the vast array of plant and animal species to the intricate ecosystems they inhabit, biodiversity encompasses the remarkable variety that exists on our planet. Each species contributes to the overall balance and functionality of the ecosystem, creating a harmonious blend of different life forms. This rich diversity not only enhances the aesthetics of nature but also plays a vital role in maintaining ecological stability.3. Heterogeneous Elements in Culture:Moving on to the cultural realm, heterogeneous elements are prevalent in the diverse traditions, customs, and beliefs that shape our societies. Different cultures bring their own unique sets of values and perspectives, enriching our collective understanding of the world. The celebration of cultural diversity fosters unity by encouraging mutual respect, appreciation, and interculturaldialogue. The exchange of ideas and experiences between cultures can lead to innovation, creativity, and greater social cohesion.4. Heterogeneous Elements in Technology:Advancements in technology also embrace heterogeneous elements. The field of artificial intelligence, for instance, combines various disciplines such as computer science, mathematics, and cognitive psychology, creating a hybrid approach toproblem-solving. By amalgamating different components, breakthroughs in technology become possible, leading to novel solutions and improvements in various aspects of human life. The power of collaboration between diverse fields of expertise is exemplified by the development of the internet, which has revolutionized communication, commerce, and the exchange of information globally.5. Heterogeneous Elements in Society:In society, heterogeneous elements can be observed in the composition of communities and organizations. A diverse workforce, for example, brings together people from differentbackgrounds, ethnicities, and skillsets. This amalgamation of perspectives and experiences enhances problem-solving capabilities, fosters creativity, and promotes inclusion. It has been proven that diverse communities and organizations perform better when it comes to innovation and adaptability, thanks to the diversity of ideas and insights brought to the table.6. Nurturing Unity Through Heterogeneous Elements:While heterogeneous elements thrive on diversity, they also have the potential to foster unity. By recognizing the value and unique contributions of each individual or component, we can build a stronger, more harmonious society. Embracing the concept of unity in diversity requires active efforts to promote inclusive practices, educate others about different perspectives, and provide platforms for open dialogue. Organizations and communities that successfully embrace heterogeneous elements are likely to experience increased creativity, productivity, and satisfaction among their members.7. Conclusion:In conclusion, the concept of a heterogeneous element serves as a powerful reminder of the richness, depth, and complexity of the world we live in. From nature's biodiversity to cultural exchanges and technological advancements, these elements symbolize the endless possibilities that arise when diversity is embraced and celebrated. By valuing and actively promoting heterogeneous elements, we can harness collective strengths, build bridges between different communities, and create a more united and inclusive global society. Let us embrace the heterogeneous element in all its forms, for it is through diversity that we truly flourish.。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
multiple levels in the architecture 8]. Another example is the RACE architecture from Mercury Computer Systems 6]. This heterogeneous platform supports an open software environment that can cross programming styles, operating systems and application programming interfaces (APIs). Our current interest is to employ the suite of machines to solve a variety of real-time signal processing applications with high communication requirements. Speci cally, the application requires predictable performance in a high-throughput sensor-driven environment. Most e orts in the literature concerning heterogeneous communication issues have focused on architectural con guration, micro-kernel operating system designs or network protocol implementations to support distributed computing environments. Our attention, however, is directed at algorithmic-level optimization for dedicated applications performed on SHHiPE systems. The key concerns are data ow among processing nodes and through memory hierarchies. Van de Velde 9] addressed the di culty of data redistribution when performed between individual computational stages. His data-distribution independent algorithms provide a suboptimal approach solution to the needs of modern embedded applications. Emerging SHHiPE systems with high performance System Area Networks (SANs), however, provide better opportunity to realize complex data ow and achieve globally optimal performance. Our group is currently developing portable, scalable algorithms on heterogeneous HPC platforms for embedded signal processing applications. The algorithm design will deal with data ow during processing, and provide high performance, exible communication. We will implement the underlying communication techniques using primitives included in the Message Passing Interface (MPI) and its extended verisons, such as MPI2 and MPI-IO. This paper is an overview of the issues currently under our study. The rest of the paper is organized as follows. Section 2 explores the architectural features of SHHiPE
Communication Issues in Heterogeneous Embedded Systems
Wenheng Liu, William J. Kostis, and Viktor K. Prasanna Department of EE-Systems, EEB-216 University of Southern California Los Angeles, CA 90089-2562
platforms and introduces a programming paradigm for signal processing on these systems. Section 3 discusses the communication requirements of high-performance signal processing applications. We use sonar signal processing as an illustrative example of the communication requirements of typical SHHiPE applications. Section 4 describes how the MPI standard can help achieve the communication requirements of embedded real-time applications. Section 5 concludes the paper.
This research was supported in part by NSF under grant DABT63-95-C-0092 and by ARPA under contract DABT63-95-C-0092. The authors can be reached by email at fliu+will+prasannag@, or at /dept/ceng/prasanna/projects/embed.html
Embedded Applications: Radar, and Sonar Signal Processing... Signal Processing Algorithmic Designs
Data Modeling, Filtering, Maximum-likelihood Estimation... Numerical methods: FFT, QRD, SVD... Basic Primitives: data layout and data redistribution methods
1 Introduction
Scalable Heterogeneous High Performance Embedded (SHHiPE) systems are fast becoming the solution of choice for real-time applications. These platforms, leveraging the high performance/cost ratio of commercial o -the-shelf (COTS) modules have become an attractive approach employed to solve scienti c problems 1]. The heterogeneous modules work in concert to reach giga op and ultimately tera op range computational power in multi-disciplinary applications. One such system is the Lockheed Martin Lab's Embedded High Performance Scalable Computing System (HPSCS) 4], which incorporates Myrinet switching technology to provide a uniform processor interconnect at
Abstract
The recent accelerated development of scalable computing systems has made possible the coordinated use of a suite of High Performance Computing (HPC) components for computationally demanding problems in embedded applications. These emerging Scalable Heterogeneous High Performance Embedded (SHHiPE) systems are designed using commercial-o the-shelf (COTS) modules. Our current interest is to employ these platforms to solve variety of problems in real-time signal processing. Large performance gains knowledge of the computational structure of an algorithm through data remapping. We present the motivation for a portable programming paradigm that captures key features of a SHHiPE platform. The Message Passing Interface (MPI) standard is proposed as a basis for development of this paradigm. An application in sonar is used to illustrate typical communication requirements in SHHiPE systems.