无线网络的业务研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
本文以业务域(包括语音、视频、音频、文本、图像等)为研究对象,构筑了一套完整的业务理论框架体系。本文的研究既可以从理论上为无线网络的业务提供性能评价指标,又可以在工程实践中完整地给出端到端的业务服务质量和用户体验质量的分析方法。本文的研究成果和技术思路可以为未来的移动互联网提供来自业务域视角的指导性建议。
     本文首先对各种常见的业务类型进行枚举、归纳和分类,并根据业务模型的不同用途,分别有针对性地提出了网络规划业务模型、排队论业务模型,源发生器业务模型和一般意义上的业务模型。这些模型的表达形式、参数、含义、用途各不相同。由于不同领域和不同层面对业务模型的需求差异太大,本文未能提出一个统一的闭式表达的数学公式来刻画业务。
     以业务模型为基本颗粒,本文提出业务容量的概念,并将其作为无线网络对业务承载能力的评价指标。业务容量是用户体验加权的用户接收速率之和的上确界。它既具有类似于网络吞吐量的效果,又具有反映用户体验的能力,还可以刻画组播、广播等通信形式对网络性能的影响。本文的研究结果表明:无线业务的速率波动程度(突发性和自相似性)、到达离开特征、上下行的不对称性、业务用户间的距离(多跳)、组播系数这几个因素对无线网络的业务容量影响最大。
     为了提前预测业务在未来一段时间内的服务质量,进而提前计算出业务容量来作为网络管理和调度的指导信息,本文进一步展开了业务流的性能分析。以“点-线-面”的逻辑思路,本文分别介绍和提出了单一业务流一跳无线链路上的性能分析、单一业务流多跳串联链路上的性能分析,以及多条并行业务流竞争一个公用网络的性能分析。基于这三个分析,本文给出了一套完整的预测分析端到端业务流服务质量的方法。
     以业务模型来刻画无线业务,以业务容量来评价无线网络,以业务流分析来预测和计算业务的服务质量。这三者合在一起,就是本文研究的从业务域出发,指导下一代无线网络规划和优化的理论体系。
     此外,本文还分析了无线业务相对于固定业务的优势和特征,展望了未来移动互联网的杀手级业务,讨论了无线业务可能的商业模式和定价策略。本文认为,在技术性因素之外,价格机制不失为一种调整网络流量、引导用户行为的好方法。
This paper took service domain as the research object, and built a theoretical framework for the communication services. This paper not only proposed a performance evaluation of wireless network in theory, but also gave an analytical method of end-to-end service quality and user experience in engineering practice. This paper's technical ideas and results could be used to guide the development of future mobile Internet.
     Firstly, this paper put various types of services into enumeration, induction and classification. And then, this paper proposed four kinds of service model respectively target to network planning, queuing theory, source generator and general sense understanding. These service models have significant differences in expression, parameter, meaning and purpose. Because of the wide difference of service model in different areas and layers, this paper failed to find a unified mathematical closed expression to describe the service model.
     Taking service model as the basic particles, this paper proposed the concept of service capacity, and put it as wireless network's performance evaluation of service supporting. Service capacity is the upper bound of user experience weighted receiver rate sum. It has a similar effect of network throughput, also has the ability to reflect the user's experience, still can describe the multicast and broadcast influence to network performance. Our research shows that:the volatility rate of wireless service (burst and self-similarity), the service arrival and leave features, the asymmetry of the uplink and downlink, the distance between users (multi-hop), the multicast coefficient, and these five factors are the greatest impact for service capacity.
     In order to predict the quality of service (QoS) in the following period and put this predict to guide the network management and schedule, this paper further expanded the service flow performance analysis. Following the "point-line-surface" logic, this paper made a series of studies, including one-hop wireless link single service flow analysis, multi-hop single service flow analysis and parallel service flows analysis. Based on the three analyses, this paper proposed a complete methodology for end-to-end QoS prediction of service flow.
     The service model is used to describe wireless service. The service capacity is used to evaluate wireless network. The service flow analysis is used to predict and calculate the QoS. Integrating three tools together, it is the theoretical system to guide the next generation wireless network's planning and optimization from service domain view.
     In addition, this paper also talked about wireless service's features respect to fixed service, looked forward to the future mobile killer service, and discussed the possible commercial model and pricing strategy for wireless service. In addition to technical factors, the price mechanism is a good way to adjust network load and guide users'behavior.
引文
[1]Lu R, Li X, Liang X, Shen X, Lin X. Is the PHY layer dead? IEEE Communications Magazine 2011; 49:159-165.
    [2]Perahia E, Stacey R. Next Generation Wireless LANs:Throughput, Robustness, and Reliability in 802.11n. Cambridge University Press 2008.
    [3]Shenker S, Clark DD, Lixia Z. Services or infrastructure:why we need a network service model. Community Networking Integrated Multimedia Services to the Home,1994, Proceedings of the 1st International Workshop on; 1994, pp.145-149,
    [4]Tang J, Zhang X. Cross-layer-model based adaptive resource allocation for statistical QoS guarantees in mobile wireless networks. IEEE Transactions on Wireless Communications 2008; 7:2318-2328.
    [5]Huang L, Kumar S, Kuo CCJ, Adaptive resource allocation for multimedia QoS management in wireless networks. IEEE Transactions on Vehicular Technology 2004; 53:547-558.
    [6]Zhou C, Honig ML, Jordan S. Utility-based power control for a two-cell CDMA data network. IEEE Transactions on Wireless Communications 2005; 4: 2764-2776.
    [7]Niyato D, Hossain E. Call-level and packet-level quality of service and user utility in rate-adaptive cellular CDMA networks:A queuing analysis. IEEE Transactions on Mobile Computing 2006; 5:1749-1763.
    [8]Shenker S. Fundamental Design Issues for the Future Internet. IEEE Journal on Selected Areas in Communications 1995; 13:1176-1188.
    [9]Lee JW, Kwon JA. Utility-Based Power Allocation for Multiclass Wireless Systems. IEEE Transactions on Vehicular Technology 2009; 58:3813-3819.
    [10]Nguyen HA, Van Nguyen T, Deokjai C. How to Maximize User Satisfaction Degree in Multi-service IP Networks. Intelligent Information and Database Systems,2009 ACIIDS 2009 First Asian Conference on; 2009. pp.471-476.
    [11]Paulski P. Kamola M. Optimal bandwidth allocation in IP network; the case of QoS-sensitive user utility functions. Performance Evaluation of Computer and Telecommunication Systems,2008 SPECTS 2008 International Symposium on; 2008. pp.421-427.
    [12]Chi Z, Honig ML, Jordan S, Berry R. Utility-based resource allocation for wireless networks with mixed voice and data services. Computer Communications and Networks,2002 Proceedings Eleventh International Conference on; 2002. pp.485-488.
    [13]Cho JW, Chong S. Utility max-min flow control using slope-restricted utility functions. IEEE Transactions on Communications 2007; 55:963-972.
    [14]Chiang M, Tan CW, Palomar DP, O'Neill D, Julian D. Power control by geometric programming. IEEE Transactions on Wireless Communications 2007; 6:2640-2651.
    [15]Lee JW, Mazumdar RR, Shroff NB. Downlink power allocation for multi-class wireless systems. IEEE/ACM Transactions on Networking 2005; 13:854-867.
    [16]Hande P, Rangan S, Chiang M, Wu XZ. Distributed Uplink Power Control for Optimal SIR Assignment in Cellular Data Networks. IEEE/ACM Transactions on Networking 2008; 16:1420-1433.
    [17]Shakkottai S, Srikant R. Economics of Network Pricing With Multiple ISPs. IEEE/ACM Transactions on Networking 2006; 14:1233-1244.
    [18]Bormann FC, Flake S, Tacken J. Business models for local mobile services enabled by convergent online charging. Mobile and Wireless Communications Summit,2007 16th IST; 2007. pp.1-5.
    [19]Bradber S, Claffy KC, Meinrath SD. The (un)Economic Internet. IEEE Computer Society 2007:53-58.
    [20]Shakkottai S, Srikant R, Ozdaglar A, Acemoglu D. The Price of Simplicity. IEEE Journal on Selected Areas in Communications,2008; 26:1269-1276.
    [21]张传福,卢辉斌,彭灿,王刚.cdma2000 1x/EV-DO通信网络规划与设计.人民邮电出版社;2009.
    [22]3GPP. TS 23.107:Quality of Service (QoS) concept and architecture.2009.
    [23]3GPP. TS 22.105:Services and Service Capabilities.2010.
    [24]Chevallier C, Brunner C, Garavaglia A. WCDMA (UMTS) Deployment Handbook Planning and Optimization Aspects. 人民邮电出版社; 2008.
    [25]段玉宏,夏国忠,胡剑,黄萍,等.TD-SCDMA无线网络设计与规划.人民邮电出版社;2007.
    [26]张传福,彭灿,李巧玲,石晋,胡熬.TD-SCDMA通信网络规划与设计.人民邮电出版社;2009.
    [27]Heffes H, Lucantoni D. A Markov Modulated Characterization of Packetized Voice and Data Traffic and Related Statistical Multiplexer Performance. IEEE Journal on Selected Areas in Communications,1986; 4:856-868.
    [28]Kaufman JS, Rege KM. Blocking in a shared resource environment with batched Poisson arrival processes. Perform Evaluation 1996; 24:249-263.
    [29]Koukoulidis V. A characterization of reversible Markov processes with applications to shared resource environments. Montreal, Canada:Concordia University; 1993.
    [30]Stamatelos GM, Koukoulidis VN. Reservation-based bandwidth allocation in a radio ATM network. IEEE/ACM Transactions on Networking 1997; 5: 420-428.
    [31]Crovella ME. Bestavros A. Self-similarity in World Wide Web traffic: Evidence and possible causes. IEEE/ACM Transactions on Networking 1997; 5:835-846.
    [32]Norros I, A Storage Model with Self-Similar Input. Queueing Syst 1994; 16: 387-396.
    [33]Paxson V, Floyd S. Wide Area Traffic-the Failure of Poisson Modeling. IEEE/ACM Transactions on Networking 1995; 3:226-244.
    [34]Leland WE, Taqqu MS, Willinger W, Wilson DV. On the Self-Similar Nature of Ethernet Traffic (Extended Version). IEEE/ACM Transactions on Networking 1994; 2:1-15.
    [35]Nayfeh AH, Lacarbonara W. On the discretization of distributed-parameter systems with quadratic and cubic nonlinearities. Nonlinear Dynam 1997; 13: 203-220.
    [36]Karagiannis T, Molle M, Faloutsos M. Long-range dependence ten years of Internet traffic modeling. IEEE Internet Computing,2004; 8:57-64.
    [37]Barabasi AL. The origin of bursts and heavy tails in human dynamics. Nature 2005; 435:207-211.
    [38]Norros I. On the Use of Fractional Brownian-Motion in the Theory of Connectionless Networks. IEEE Journal on Selected Areas in Communications 1995; 13:953-962.
    [39]Riedi RH, Crouse MS, Ribeiro VJ, Baraniuk RG. A multifractal wavelet model with application to network traffic. IEEE Transactions on Information Theory 1999; 45:992-1018.
    [40]Yantai S, Huifang F, Hua W, Maode M. FARIMA model based admission control to support QoS service in the networks with WiFi access. Mobile Technology, Applications and Systems,2005 2nd International Conference on; 2005. pp.6 pp.-6.
    [41]Muscariello L, Mellia M, Meo M, Marsan MA, Lo Cigno R. Markov models of internet traffic and a new hierarchical MMPP model. Comput Commun 2005; 28:1835-1851.
    [42]Willinger W, Taqqu MS, Sherman R, Wilson DV. Self-similarity through high-variability:Statistical analysis of ethernet LAN traffic at the source level. IEEE/ACM Transactions on Networking 1997; 5:71-86.
    [43]Zhi Q, Jong-Moon C. Priority queueing analysis of self-similar in high-speed networks. Communications,2003 ICC'03 IEEE International Conference on; 2003. pp.1606-1610 vol.1603.
    [44]Jin XL, Min GY. Modelling and Analysis of Priority Queueing Systems with Multi-Class Self-Similar Network Traffic:A Novel and Efficient Queue-Decomposition Approach. IEEE Transactions on Communications 2009; 57:1444-1452.
    [45]倪锐,卫国,秦晓卫.一种自相似网络业务的生成方法.中国:国家知识产权局;2009.
    [46]Shannon CE. The mathematical theory of communication. The Bell System Technical Journal 1948; 27:379-423.
    [47]Rui N, Xiaowei Q, Wuyang Z, Guo W. A novel communication service modeling. Wireless Information Technology and Systems (ICWITS),2010 IEEE International Conference on; 2010. pp.1-4.
    [48]Angrisani L, Napolitano A, Vadursi M. Modeling and Measuring Link Capacity in Communication Networks. IEEE Transactions on Instrumentation and Measurement 2010; 59:1065-1072.
    [49]姜丹.信息论与编码.中国科学技术大学出版社;2001.
    [50]Prasad R, Dovrolis C, Murray M, Claffy K. Bandwidth estimation:metrics, measurement techniques, and tools. Ieee Network 2003; 17:27-35.
    [51]Viterbi AM, Viterbi AJ. Erlang Capacity of a Power Controlled Cdma System. IEEE Journal on Selected Areas in Communications 1993; 11:892-900.
    [52]Kelly F. Notes on effective bandwidths. Stochastic Networks:Theory and Applications. New York:Oxford University Press; 1996.
    [53]Chang CS. Performance Guarantees in Communication Networks New York: Spring-Verlog; 2000.
    [54]许宏敏,李青,祝绘青,孙玉兰,谢永斌.TD-SCDMA无线网络原理及方法.人民邮电出版社:2009.
    [55]Gupta P, Kumar PR. The capacity of wireless networks. IEEE Transactions on Information Theory 2000; 46:388-404.
    [56]Xie LL, Kumar PR. A network information theory for wireless communication: Scaling laws and optimal operation. IEEE Transactions on Information Theory 2004; 50:748-767.
    [57]Xue F, Xie LL, Kumar PR. The transport capacity of wireless networks over fading channels. IEEE Transactions on Information Theory 2005; 51:834-847.
    [58]Ahmad SHA, Jovicic A, Viswanath P. On outer bounds to the capacity region of wireless networks. IEEE Transactions on Information Theory 2006; 52: 2770-2776.
    [59]Xie LL, Kumar PR. On the path-loss attenuation regime for positive cost and linear scaling of transport capacity in wireless networks. IEEE Transactions on Information Theory 2006; 52:2313-2328.
    [60]Aeron S, Saligrama V. Wireless ad hoc networks:Strategies and scaling laws for the fixed SNR regime. IEEE Transactions on Information Theory 2007; 53: 2044-2059.
    [61]Franceschetti M. A note on Leveque and Telatar's upper bound on the capacity of wireless ad hoc networks. IEEE Transactions on Information Theory 2007; 53:3207-3211.
    [62]Franceschetti M, Dousse O, Tse DNC, Tniran P. Closing the gap in the capacity of wireless networks via percolation theory. IEEE Transactions on Information Theory 2007; 53:1009-1018.
    [63]Ozgur A, Leveque O, Preissmann E. Scaling laws for one- and two-dimensional random wireless networks in the low-attenuation regime. IEEE Transactions on Information Theory 2007; 53:3573-3585.
    [64]Nebat Y, Cruz RL, Bhardwaj S. The Capacity of Wireless Networks in Nonergodic Random Fading. IEEE Transactions on Information Theory,2009; 55:2478-2493.
    [65]Andrews JG, Weber S, Kountouris M, Haenggi M. Random access transport capacity. IEEE Transactions on Wireless Communications,2010; 9: 2101-2111.
    [66]Kilkki K. Quality of experience in communications ecosystem. Journal of Universal Computer Science 2008; 14:615-624.
    [67]ITU-T. Definition of Quality of Experience (QoE).2007.
    [68]Soldani D, Li M, Cuny R. QoS and QoE management in UMTS Cellular Systems. Wiley Print; 2006.
    [69]Shakkottai S, Srikant R, Ozdaglar A, Acemoulu D. The price of simplicity. IEEE Journal on Selected Areas in Communications 2008; 26:1269-1276.
    [70]ITU-T. Recommendation "G.1010":End-user multimedia QoS categories. 2001.
    [71]OSI. ISO/IEC 7498-1:Basic Reference Model:The Basic Model.1994.
    [72]Tasaka S, Ishibashi Y. Mutually compensatory property of multimedia QoS. Communications,2002 ICC 2002 IEEE International Conference on; 2002. pp. 1105-1111 vol.1102.
    [73]Mi Sun R, Hong-Shik P, Sang-Chul S. QoS class mapping over heterogeneous networks using Application Service Map. Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies,2006 ICN/ICONS/MCL 2006 International Conference on; 2006. pp.13-13.
    [74]ITU-T. Recommendation "Y.1541":Network performance objectives for IP-based services.2006.
    [75]Resta G, Santi P. WiQoSM:An integrated QoS-aware mobility and user Behavior model for wireless data networks. IEEE Transactions on Mobile Computing 2008; 7:187-198.
    [76]Injong R, Minsu S, Seongik H, Kyunghan L, Song C. On the Levy-Walk Nature of Human Mobility. INFOCOM 2008 The 27th Conference on Computer Communications IEEE; 2008. pp.924-932.
    [77]Changho S, Jeonghoon M. Resource Allocation for Multicast Services in Multicarrier Wireless Communications. IEEE Transactions on Wireless Communications,2008; 7:27-31.
    [78]Gradshteyn IS, Ryzhik IM. Table of Integrals, Series, and Products. New York: Academic Press,7th ed.; 2007.
    [79]3GPP. TS 26.346:Multimedia Broadcast Multicast Service.2009.
    [80]Byers JW, Luby M, Mitzenmacher M. A digital fountain approach to asynchronous reliable multicast. IEEE Journal on Selected Areas in Communications,2002; 20:1528-1540.
    [81]Michael L, Tiago G, Thomas S, Mark W, Reliable Multimedia Download Delivery in Cellular Broadcast Networks. IEEE Transactions on Broadcasting, 2007; 53:235-246.
    [82]Gomez-Barquero D, Fernandez-Aguilella A, Cardona N. Multicast Delivery of File Download Services in Evolved 3G Mobile Networks With HSDPA and MBMS. IEEE Transactions on Broadcasting,2009; 55:742-751.
    [83]Jeong Geun K, Krunz MM. Bandwidth allocation in wireless networks with guaranteed packet-loss performance. IEEE/ACM Transactions on Networking. 2000; 8:337-349.
    [84]Krunz MM, Jeong Geun K. Fluid analysis of delay and packet discard performance for QoS support in wireless networks. IEEE Journal on Selected Areas in Communications.2001; 19:384-395.
    [85]Boudec J-YL, Thiran P. Network Calculus:A Theory of Deterministic Queuing Systems for the Internet. Springer-Verlag 2001.
    [86]Le Boudec JY. Application of network calculus to guaranteed service networks. IEEE Transactions on Information Theory 1998; 44:1087-1096.
    [87]Starobinski D, Karpovsky M, Zakrevski LA. Application of network calculus to general topologies using turn-prohibition. IEEE/ACM Transactions on Networking 2003; 11:411-421.
    [88]Ciucu F, Burchard A, Liebeherr J. Scaling properties of statistical end-to-end bounds in the network calculus. IEEE Transactions on Information Theory 2006:52:2300-2312.
    [89]Gulyas A, Biro J. A stochastic extension of network calculus for workload loss examinations. IEEE Communication Letter 2006; 10:399-401.
    [90]Li CZ. Burchard A. Liebeherr J. A network calculus with effective bandwidth. IEEE/ACM Transactions on Networking 2007; 15:1442-1453.
    [91]Fidler M. A Survey of Deterministic and Stochastic Service Curve Models in the Network Calculus. IEEE Communications Surveys and Tutorials 2010; 12: 59-86.
    [92]张信明,陈国良,顾军.基于网络演算计算保证服务端到端延迟上界.软件学报2001;12:889-893.
    [93]李庆华,陈志刚,张连明,曾峰,李翔.基于网络演算的无线自组网QoS性能确定上界研究.通信学报 2008;29:32-39.
    [94]Chang CS. Performance Guarantees in Communication Networks. New York: Spring-Verlog; 2000.
    [95]Ravindra K Ahuja, Magnanti TL, Orlin J. Network Flows:Theory, Algorithms and Application. Pressed by Prentice Hall; 1993.
    [96]谢金星,刑文训,王振波.网络优化.清华大学出版社;2009.
    [97]E.M. S, E.L. G, M.K. J. Evaluation of QoS in UMTS Backbone Network Using Differentiated Services. NRSC'08; 2008.
    [98]Dutta G, D. D. Performance Study of an optical Backbone MAC Interconnecting WiMAX Base Stations over A City/County Area. WOCN'08; 2008. pp.1-6.
    [99]Yang W, Yi-chun Z, Shao-hua Y. Brownian Motion Based Queuing Analysis and Bandwidth Prediction for Aggregated Domain in Backbone Networks. ChinaCom'07; 2007. pp.223-227.
    [100]托米.T.艾荷南.如何从3G业务中获利.北京:清华大学出版社;2010.
    [101]Nicholas E. The Economics of networks. International Journal of Industrial Organization 1996; 14:673-699.
    [102]Nagurney A. Network Economics. Pressed by John Wiley & Sons, Chichester, UK; 2009.
    [103]Odlyzko AM. Paris metro pricing for the Internet. ACM Conference on Electronic Commerce; 1999. pp.140-147.
    [104]Lee D, Mo J, Park J. Analysis of Paris Metro Pricing for Wireless Internet Services. Information Networking (ICOIN),2011 International Conference on; 2011. pp.120-125.
    [105]Courcoubetis C, Weber R. Pricing Communication Networks:Economics, Technology and Modeling. WILEY Press; 2003.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700