无线传感器网络若干关键技术研究
|
摘要
无线传感器网络由大量具有数据感知、信息处理和无线通信能力的传感节点组成，节点间以无线多跳的无中心方式连接，它集合了传感测量、微电机系统、嵌入式计算以及网络通信等多种学科，是一门新兴综合性科学技术。无线传感器网络以数据为中心、强调信息的感知和协同处理，提供了一种全新的信息获取和处理方法，在国防军事、安全反恐、环境监测、交通管理、医疗卫生和生产制造等领域具有广阔应用前景。然而，网络节点数量众多，资源和处理能力有限，维护困难且性能难以保证，数据高度冗余，应用环境复杂多样，这些特点从基础理论和工程技术两个层面给网络协议设计和信息处理带来巨大挑战，相关研究受到越来越多研究者的关注。正是在这样的背景下，本文结合国防科工委基础科研项目、教育部博士点基金项目和国家自然科学基金项目，围绕网络协议设计和协作信号信息处理，对无线传感器网络环境下的若干关键技术进行了系统、深入的研究。主要研究内容和成果如下：
(1) 无线传感器网络及其关键技术深入分析了无线传感器网络的特点，给出了网络体系结构、形式化描述和研究域框架。对网络协议设计、协作信号信息处理和网络模拟仿真等关键技术在传感器网络环境下所面临的挑战、解决方法和已有成果进行了深入研究。
(2) 无线传感器网络能量敏感路由协议——能耗均衡的能量敏感多径路由算法 针对无线传感器网络流量负载非均匀分布和可能存在不同性能需求流量的特点，在建立网络能量消耗模型和定义网络生存期的基础上，提出了一种基于能耗均衡的能量敏感多径路由算法EBEMR。该算法以时空能耗均衡为主要目标，选取节点剩余能量、节点间传输能耗和时延3种度量，组合设计了最大最小路径节点剩余能量、最小路径传输能耗和最小跳策略；针对实时和普通流量不同的性能需求，选择不同传输路径，避免过度使用部分节点，对相同类型流量，设计能量敏感的波尔兹曼函数完成路径切换：利用物理层和MAC层信息进行了交叉层优化。仿真实验表明，在不同或相同性能要求流量情况下，算法能很好地进行服务区分或路径选择，实现能量在全网的均衡使用，大大提高网络生存期。
(3) 无线传感器网络移动Agent机制——基于移动Agent的传感器网络框架模型与基于定向扩散的移动Agent机制实现针对无线传感器网络中传统C／S计算模式存在的资源浪费、负载不均衡、容错性和安全性较差等缺陷，从网络和节点两个层面提出了一种基于移动Agent的传感器网络框架模型，给出了模型组成、功能定义和交互接口。在此基础上，提出了一种基于定向扩散的移动Agent
Recent advances in sensor, micro-electro-mechanical systems (MEMS) technology, nested computation and wireless communications have enabled the development of wireless sensor networks (WSNs) including a large number sensor nodes, which consistint of sensing, data processing, and communicating components. WSNs, which are data-centric and put emphasis upon information detection and cooperative processing, provide a novel technology about acquiring and processing information. WSNs is capable of the detection, measurement, classification, recognition, location and track of interested target, and can be widely used in national defense, infrastructure security, environment monitoring, traffic management and industry control applications etc. But its characters of so many nodes, redundant data, complicated enviroments and limited resources, especially node energy and communication bandwidth, have presented great challenges for its basic theory and engineering technology. Network protocol stack and collabrative signal and information processing (CSIP), which are the important components of key technologies in wireless sensor network, have attracted more and more attentions. Therefore, technologies of network protocol design and information processing are systemically and deeply investigated in this dissertation. The research work and the main results are as follows:
(1) Wireless sensor networks and key technologies The characteristics of WSNs and the difficulties encountered by the traditional network protocols used in WSNs are first analyzed. Then based on the presentation of network model and formal description, key technologies of protocol design, CSIP and network simulation are carefully studied and the main research advances are detailedly reviewed.
(2) Energy-load balancing based engergy-aware multipath routing In
avoidance of some nodes becoming inactive too early resulting from the nonuniform distribution of traffic in WSNs, the Energy-load Balancing based Engergy-aware Multipath Routing (EBEMR) algorithm is proposed. According to the two metrics of energy left and hops, strategies of Maximum of Minimum of Path node-Energy (MaxMPRE) and Minimum of Hop-Count (MHC) are designed. For the diverse kinds of data traffic, the algorithm can choose different pathes to avoid some nodes overworking, and for the same data traffic, it smooths the jitters generated by the path-switch based on the Boltzmann function to improve the communication performance. The experiment results show that EBEMR outperforms the Directed
(1) 无线传感器网络及其关键技术深入分析了无线传感器网络的特点，给出了网络体系结构、形式化描述和研究域框架。对网络协议设计、协作信号信息处理和网络模拟仿真等关键技术在传感器网络环境下所面临的挑战、解决方法和已有成果进行了深入研究。
(2) 无线传感器网络能量敏感路由协议——能耗均衡的能量敏感多径路由算法 针对无线传感器网络流量负载非均匀分布和可能存在不同性能需求流量的特点，在建立网络能量消耗模型和定义网络生存期的基础上，提出了一种基于能耗均衡的能量敏感多径路由算法EBEMR。该算法以时空能耗均衡为主要目标，选取节点剩余能量、节点间传输能耗和时延3种度量，组合设计了最大最小路径节点剩余能量、最小路径传输能耗和最小跳策略；针对实时和普通流量不同的性能需求，选择不同传输路径，避免过度使用部分节点，对相同类型流量，设计能量敏感的波尔兹曼函数完成路径切换：利用物理层和MAC层信息进行了交叉层优化。仿真实验表明，在不同或相同性能要求流量情况下，算法能很好地进行服务区分或路径选择，实现能量在全网的均衡使用，大大提高网络生存期。
(3) 无线传感器网络移动Agent机制——基于移动Agent的传感器网络框架模型与基于定向扩散的移动Agent机制实现针对无线传感器网络中传统C／S计算模式存在的资源浪费、负载不均衡、容错性和安全性较差等缺陷，从网络和节点两个层面提出了一种基于移动Agent的传感器网络框架模型，给出了模型组成、功能定义和交互接口。在此基础上，提出了一种基于定向扩散的移动Agent
Recent advances in sensor, micro-electro-mechanical systems (MEMS) technology, nested computation and wireless communications have enabled the development of wireless sensor networks (WSNs) including a large number sensor nodes, which consistint of sensing, data processing, and communicating components. WSNs, which are data-centric and put emphasis upon information detection and cooperative processing, provide a novel technology about acquiring and processing information. WSNs is capable of the detection, measurement, classification, recognition, location and track of interested target, and can be widely used in national defense, infrastructure security, environment monitoring, traffic management and industry control applications etc. But its characters of so many nodes, redundant data, complicated enviroments and limited resources, especially node energy and communication bandwidth, have presented great challenges for its basic theory and engineering technology. Network protocol stack and collabrative signal and information processing (CSIP), which are the important components of key technologies in wireless sensor network, have attracted more and more attentions. Therefore, technologies of network protocol design and information processing are systemically and deeply investigated in this dissertation. The research work and the main results are as follows:
(1) Wireless sensor networks and key technologies The characteristics of WSNs and the difficulties encountered by the traditional network protocols used in WSNs are first analyzed. Then based on the presentation of network model and formal description, key technologies of protocol design, CSIP and network simulation are carefully studied and the main research advances are detailedly reviewed.
(2) Energy-load balancing based engergy-aware multipath routing In
avoidance of some nodes becoming inactive too early resulting from the nonuniform distribution of traffic in WSNs, the Energy-load Balancing based Engergy-aware Multipath Routing (EBEMR) algorithm is proposed. According to the two metrics of energy left and hops, strategies of Maximum of Minimum of Path node-Energy (MaxMPRE) and Minimum of Hop-Count (MHC) are designed. For the diverse kinds of data traffic, the algorithm can choose different pathes to avoid some nodes overworking, and for the same data traffic, it smooths the jitters generated by the path-switch based on the Boltzmann function to improve the communication performance. The experiment results show that EBEMR outperforms the Directed
引文
① 如无特别说明，本文不刻意区分“传感器网络”和“无线传感器网络”。
② 严格说来，模拟(simulation)和仿真(emulation)是有区别的，但已在事实上长期相互混用。如无特别说明，本文不区分“模拟”和“仿真”，统一使用“仿真”一词，强调模拟系统过程的某些行为特征。
① 数据分组包(Packet)，又称包、分组或报文。
① Agent，国内尚未有统一翻译，可称为主体、代理或智能体等，这里保留不译。
① MAE，也有学者译为移动Agent服务设施，它与MAP含义相同，指移动Agent的运行支撑环境或平台。
[1] D. Estrin, R. Govindan, J. Heidemann, et al. Next Century Challenges: Scalable Coordination in Sensor Networks. Proc. 5th ACM/IEEE International Conference on Mobile Computing and Networking, Seattle, WA, USA, 1999: 263-270.
[2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, et al. Wireless Sensor Networks: A Survey. Computer Networks, 2002, 38: 393-422.
[3] S. Kumar, F. Zhao, D. Shepherd. Collaborative Signal and Information Processing in Microsensor Networks. IEEE Signal Processing Magazine, 2002, 19(2): 13-14.
[4] C. Y. Chong, S. Kumar. Sensor Networks Evolution, Opportunities, and Challenges. Proc. IEEE, 2003, 91(8): 1247-1256.
[5] 孙利民，李建中，陈渝，等．无线传感器网络．北京，清华大学出版社，2005．
[6] P. Coy, N. Gross. 21 Ideas for the 21st Century. Business Week Magazine, 1999, http://www.businessweek.com/1999/99_35/b3644024.htm.
[7] 10 Emerging Areas of Technology. MIT Technology Review Magazine, 2003, http://www.technologyreview.com.
[8] G. J. Pottie, W. J. Kaiser. Embedding the Internet: Wireless Integrated Network Sensors. Communications of the ACM, 2000, 43(5): 51-58.
[9] 王金龙，王呈贵，吴启辉，等．Ad Hoc移动无线网络．北京，国防工业出版社，2004．
[10] 郑少仁，王海涛，赵志峰，等．Ad Hoc网络技术．北京，人民邮电出版社，2005．
[11] R. Rashid, G. Robertson. Accent: A Communication Oriented Network Operating System Kernel. Proc. 8th Symposium on Operating System Principles, Pacific Grove, CA, USA, 1981: 64-75.
[12] R. Rashid, D. Julin, D. Orr, et. al. Mach: A System Software Kernel. Proc. 34th IEEE Computer Society International Conference, San Francisco, CA, USA, 1989: 176-178.
[13] C. Myers, A. Oppenheim, R. Davis, et. al. Knowledge Based Speech Analysis and Enhancement. Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, San Diego, CA, USA, 1984: 39-42.
[14] R. T. Lacoss. Distributed Mixed Sensor Aircraft Tracking. Proc. American Control Conference, Minneapolis, MN, USA, 1987: 1827-1830.
[15] D. Alberts, J. Garstka, F. Stein. Network Centric Warfare, 1999, http://www.dodccrp.org/publications/pdf/Alberts_NCW.pdf.
[16] WINS Project. http://www.janet.ucla.edu/WINS/.
[17] Smart Dust Project. http://robotics.eecs.berkeley.edu/～pister/SmartDust.
[18] NEST Project. http://webs.cs.berkeley.edu/nest-index.html.
[19] The Cooperative Engagement Capability. Johns Hopkins APL Technical Digest, 1995, 16(4): 377-396. http://techdigest.jhuapl.edu/td1604/APLteam.pdf.
[20] Y. Carts-Powell. Unattended Ground Sensors Stop and Analyze the Roses. OE Reports, 2000, http://www.spie.org/web/oer/april/apr00/cover2.html.
[21] D. Caterinicchia. DARPA Developing Killer Tech. FCW.COM, 2002. http://www.fcw.com/article76811.
[22] SensIT Project. http://www.sainc.com/sensit/.
[23] J. L. Paul. Smart Sensor Web: Web-based Exploitation of Sensor Fusion for Visualization of the Tactical Battlefield. IEEE Aerospace and Electronic Systems Magazine, 2001, 16(5): 29-36.
[24] ALERT System. http://www.altersystem.org/.
[25] Habitat Monitoring on Great Duck Island. http://www.greatduckisland.net.
[26] L. Schwiebert, S. Gupta, J. Weinmann. Research Challenges in Wireless Networks of Biomedical Sensors. Proc. 7th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Rome, Italy, 2001: 151-165.
[27] S. Meyer, A. Rakotonirainy. A Survey of Research on Context-Aware Homes. Proc. Australasian information security workshop conference on ACSW frontiers 2003, Adelaide, Astralia, 2003, 21: 159-168.
[28] AHRI Project. http://www.cc.gatech.edu/fce/ahri.
[29] NASA/JPL Sensor Webs Project. http://sensorwebs.jpl.nasa.gov/.
[30] CENS Project. http://research.cens.ucla.edu/.
[31] SensoNet Project. http://www.ece.gatech.edu/research/labs/bwn/Sensor/.
[32] Broadband & Wireless Networking Laboratory. http://www.ece.gatech.edu/research/labs/bwn/.
[33] COUGAR Project. http://www.cs.cornell.edu/database/cougar/index.htm.
[34] 任丰原，黄海宁，林闯．无线传感器网络．软件学报，2003，14(7)：1282-1291．
[35] 国家中长期科学和技术发展规划纲要(2006-2020)．http://www.gov.cn/jrzg/2006-02/09/content_183787.htm.
[36] 李建中，李金宝，石胜飞．传感器网络及其数据管理的概念，问题与进展．软件学报，2003，14(10)：1717-1727．
[37] 崔莉，鞠海玲，苗勇等．无线传感器网络研究进展．计算机研究与发展，2005，42(1)：163-174．
[38] 马祖长，孙怡宁，梅涛．无线传感器网络综述．通信学报，2004，25(4)：114-124．
[39] 徐雷鸣，庞博，赵耀．NS与网络模拟．北京，人民邮电出版社，2003．
[40] W. Ye, J. Heidemann, D. Estrin. An Energy-efficient Mac Protocol for Wireless Sensor Networks. Proc. 21th International Annual Joint Conference of the IEEE Computer and Communications Societies, New York, NY, USA, 2002: 1567-1576.
[41] W. Ye, J. Heidemann, D. Estrin. Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 2004, 12(3): 493-506.
[42] T. Van Dam, K. Langendoen. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 171-180.
[43] V. Rajendran, K. Obraczka, J. J. Garcia-Luna-Aceves. Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 181-192.
[44] C. C. Enz, A. El-Hoiydi, J.-D. Decotignie, et al. WiseNET: An Ultralow-Power Wireless Sensor Network Solution. IEEE Computer, 2004, 37(8): 62-70.
[45] J. Polastre, J. Hill, D. Culler. Versatile Low Power Media Access for Wireless Sensor Networks. Proc. 2nd ACM Conference on Embedded Networked Sensor Systems, Baltimore, MD, USA, 2004: 95-107.
[46] S. Hedetniemi, A. Liestman. A Survey of Gossiping and Broadcasting in Communication Networks. Networks, 1988, 18(4): 319-349.
[47] W. Heinzelman, A. Chandrakasan, H. Balakrishnan. Energy-Efficient Communication Protocol for Wireless Microsensor Networks. Proc. 33rd Annual Hawaii International Conference on System Sciences, Maui, Hawaii, USA, 2000: 4-7.
[48] K. Akkaya, M. Younis. A Survey on Routing Protocols for Wireless Sensor Networks. Ad Hoc Networks, 2005, 3(3): 325-349.
[49] J. Kulik, W. Rabiner, H. Balakrishnan. Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. Proc. 5th ACM/IEEE Mobicom Conference, seattle, WA, USA, 1999: 174-185.
[50] C. Intanagonwiwat, R. Govinda, D. Estrin. Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks. Proc. 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Boston, MA, 2000: 56-67.
[51] C. Intanagonwiwat, R. Govinda, D. Estrin, et al. Directed Diffusion for Wireless Sensor Networking. IEEE/ACM Transactions on Networking, 2002, 11(1): 2-16.
[52] F. Silva, J. Heidemann, R. Govindan, et al. Directed Diffusion. Technical Report, ISI-TR-2004-586, USC/Information Sciences Institute, 2004.
[53] D. Niculescu. Positioning in Ad Hoc Sensor Networks. IEEE Network, 2004, 18(4): 24-29.
[54] I. Stojmenovic. Position Based Routing in Ad Hoc Networks. IEEE Communications Magazine, 2002, 40(7): 128-134.
[55] Y. Yu, R. Govindan, D. Estrin. Geographical and Energy-Aware Routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks. Technical Report, UCLA-CSD TR-01-0023, UCLA Computer Science Department, 2001.
[56] D. D. Clark, D. L. Tennenhouse. Architectural Considerations for a New Generation of Protocols. Proc. ACM Symposium on Communications Architectures and Protocols, Philadelphia, PA, USA, 1990: 200-208.
[57] M. B. Abbott, L. L. Peterson. Increasing Network Throughput by Integrating Protocol Layers. IEEE/ACM Transactions on Networking, 1993, 1(5): 600-610.
[58] Yu-Chee Tseng, Ten-Yueng Hsieh. Fully Power-Aware and Location-Aware Protocols for Wireless Multi-hop Ad Hoc Networks. Proc. 11th International Conference on Computer Communications and Networks, Miami, FL, USA 2002:608-613.
[59] R. Madan, S. Cui, S. Lall, et al. Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks. Proc. 24th International Annual Joint Conference of the IEEE Computer and Communications Societies, Miami, FL, USA, 2005: 1964-1975.
[60] D. Puccinelli, E. Sifakis, M. Haenggi. A Cross-Layer Approach to Energy Balancing in Wireless Sensor Networks. Proc. Workshop on Networked Embedded Sensing and Control, Notre Dame, IN, USA, 2005.
[61] M. L. Sichitiu. Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks. Proc. 23rd International Annual Joint Conference of the IEEE Computer and Communications Societies, HongKong, China, 2004: 1740-1750.
[62] L. P. Clare, E. H. Jennings, J. L. Ciao. Performance Evaluation Modeling of Networked Sensors. Proc. IEEE Aerospace Conference, Big Sky, Montana, USA, 2003: 1313-1322.
[63] J.-J. Lee, B. Krishnamachari, C.-C. J. Kuo. Impact of Heterogeneous Deployment on Lifetime Sensing Coverage in Sensor Networks. Proc. 1st IEEE Conference on Sensor and Ad Hoc Communications and Networks, Santa Clara, CA, USA, 2004: 367-376.
[64] A. Ghosh. Estimating Coverage Holes and Enhancing Coverage in Mixed Sensor Networks. Proc. 29th Annual IEEE International Conference on Local Computer Networks, Tampa, FL, USA, 2004: 68-76.
[65] Y. Zou, K. Chakrabarty. A Distributed Coverage- and Connectivity-Centric Technique for Selecting Active Nodes in Wireless Sensor Networks. IEEE Transactions on Computers, 2005, 54(8):978:991.
[66] T. Yan, T. He, J. A. Stankovic. Differentiated Surveillance for Sensor Networks. Proc. 1st ACM international conference on Embedded networked sensor systems, Los Angeles, CA, USA, 2003:51-62.
[67] C.-F. Huang, L.-C. Lo, Y.-C. Tseng, et al. Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks. Proc. IEEE International Symposium on Circuits and Systems, Kobe, Japan, 2005: 640-643.
[68] K. Barr, K. Asanovic. Energy Aware Lossless Data Compression. Proc. 1st International Conference on Mobile Systems, Applications and Services, San Francisco, CA, USA, 2003: 231-244.
[69] S. S. Pradhan, J. Kusuma, K. Ramchandran. Distributed Compression in a Dense Microsensor Network. IEEE Signal Processing Magazine, 2002, 19(2):51-60.
[70] J. Chou, D. Petrovic, K. Ramachandran. A Distributed and Adaptive Signal Processing Approach to Reducing Energy Consumption in Sensor Networks. Proc. 22nd International Annual Joint Conference of the IEEE Computer and Communications Societies, San Francisco, CA, USA, 2003:1054-1062.
[71] J. N. Laneman, G. W. Wornell. Distributed Space-Time-Coded Protocols for Exploiting Cooperative Diversity in Wireless Networks. IEEE Transactions on Information Theory, 2003, 49(10): 2415-2425.
[72] M. Haenggi. Twelve Reasons Not to Route over Many Short Hops. Proc. IEEE Vehicular Technology Conference, Los Angeles, CA, USA, 2004: 3130-3134.
[73] M. Haenggi. Analysis and Design of Diversity Schemes for Ad Hoc Wireless Networks. IEEE Journal on Selected Areas in Communications, 2003, 23(1):19-27.
[74] D. Petrovic, R. C. Shah, K. Ramchandran, et al. Data Funneling: Routing with Aggregation and Compression for Wireless Sensor Networks. Proc. 1st IEEE International Workshop on Sensor Network Protocols and Applications, Anchorage, AL, 2003: 156-162.
[75] T. Arici, B. Gedik, Y. Altunbasak, et al. PINCO: a Pipelined In-Network Compression Scheme for Data Collection in Wireless Sensor Networks. Proc. 12th International Conference on Computer Communications and Networks, Dallas, TX, USA, 2003: 539-544.
[76] S. J. Baek, G. de Veciana, Xun Su. Minimizing Energy Consumption in Large-scale Sensor Networks through Distributed Data Compression and Hierarchical Aggregation. IEEE Journal on Selected Areas in Communications, 2004, 22(6): 1130-1140.
[77] L. J. Guibas. Sensing, Tracking and Reasoning with Relations. IEEE Signal Processing Magazine, 2002, 19(2): 73-85.
[78] F. Zhao, J. Zhin, J. Reich. Information-Driven Dynamic Sensor Collaboration. IEEE Signal Processing Magazine. 2002, 19(2): 61-72.
[79] F. Zhao, J. Liu, J. Liu, et al. Collaborative Signal and Information Processing: an Information-Directed Approach. Proc. IEEE, 2003, 91(8): 1199-1209.
[80] H. Qi, S. Iyengar, K. Chakrabarty. Multiresolution Data Integration using Mobile Agents in Distributed Sensor Networks. IEEE Transactions on Systems, Man and Cybernetics, 2001, 31(3): 383-391.
[81] H. Qi, Y. Xu, X. Wang. Mobile-Agent-based Collaborative Signal and Information Processing in Sensor Networks. Proc. IEEE, 2003, 91(8): 1172-1183.
[82] Q. Wu, N. S. V. Rao, J. Barhen, et al. On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks. IEEE Transaction on Knowledge and Data Engineering, 2004, 16(6): 740-753.
[83] J. Liu, M. Chu, J. Reich, et al. State-Centric Programming for Sensor-Actuator Network Systems. IEEE Pervasive Computing, 2003, 2(4): 50-62.
[84] Opnet.http://www.opnet.com/.
[85] QualNet. http://www.scalable-networks.com/.
[86] OMNET++. http://www.omnetpp.org/index.php.
[87] NS-2. http://www.isi.edu/nsnam/dist/.
[88] Glomosim. http://pcl.cs.ucla.edu/projects/glomosim/.
[89] SensorSim. http://nesl.ee.ucla.edu/projects/sensorsim/.
[90] SENSIM. http://csc.lsu.edu/sensor_web/simulator.html.
[91] NRL SernsorSim. http://nrlsensorsim.pf.itd.nrl.navy.mil/.
[92] P. Levis, N. Lee, M. Welsh, et al. TOSSIM: Accurate and scalable simulation of entire TinyOS applications. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 126-137.
[93] S. Chen. Routing Support for Providing Guaranteed End-to-End Quality-of-Service. Phd Thesis, University of Illino, 1999.
[94] T. S. Rappaport. Wireless Communications Principles and Practices, Second Edition. Beijing, Publishing House of Electronics Industry, 2004.
[95] E. S. Sousa, J. A. Silvester. Optimum Transmission Ranges in a Direct-Sequence Spread Spectrum Multihop Packet Radio Network. IEEE Journal on Selected Areas in Communications, 1990, 8(5): 762-771.
[96] P. Gupta, P. R. Kumar. The Capacity of Wireless Networks. IEEE Transactions on Information Theory, 2000, 46(2): 388-404.
[97] J.-H. Chang, L. Tassiulas. Energy Conserving Routing in Wireless Ad-hoc Networks. Proc. 19th International Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel, 2000: 22-31.
[98] A. Shankar, Z. Liu. Maximum Lifetime Routing in Wireless Ad-hoc Networks. Proc. 23th International Annual Joint Conference of the IEEE Computer and Communications Societies, Hongkong, 2004, 12(4): 609-619.
[99] M. R. Pearlman, J. Deng, B. Liang, et al. Elective Participation in Ad Hoc Networks Based on Energy Consumption. Proc. IEEE Global Telecommunications Conference and Symposium on Ad-Hoc Wireless Networks, Taipei, Taiwan, 2002: 26-31.
[100] A. Sinhua, A. Chandrakasan. Dynamic Power Management in Wireless Sensor Network. IEEE Design and Test of Computer, 2001, 18(2): 62-74.
[101] C. LM, H. Kim, S. Ha. Dynamic Voltage Scheduling Technique for Low-power Multimedia Application Using Buffers. Proc. International Symposium on Low Power Electronics and Design. Huntington Beach , CA, USA, 2001: 34-39.
[102] V. Rodoplu, T. H. Meng. Minimum Energy Mobile Wireless Networks. IEEE Journal on Selected Areas in Communications, 1999, 17(8): 1333-1344.
[103] L. Li, JY Halpern. Minimum Energy Mobile Wireless Networks revisited. Proc. IEEE International Conference on Communications (ICC), Helsinki, Finland, 2001:278-283.
[104] J.-H. Chang, L. Tassiulas. Maximum Lifetime Routing in Wireless Sensor Networks. IEEE/ACM Transaction on Networking, 2004, 12(4): 609-619.
[105] M. Haenggi. Energy-Balancing Strategies for Wireless Sensor Networks. Proc. IEEE International Symposium on Circuits and Systems, Bangkok, Thailand, 2003:828-831.
[106] V. Rodoplu, T. H. Meng. Minimum Energy Mobile Wireless Networks. IEEE Journal on Selected Areas in Communications, 1999, 8(17): 1333-1344.
[107] C. Intanagonwiwat, D. Estrin, R. Govindan, et al. Impact of Network Density on Data Aggregation in Wireless Sensor Networks. Proc. 22nd International Conference on Distributed Computing Systems, Vienna, Austria, 2002: 457-458.
[108] S. Singh, M. Woo, C. S. Raghavendra. Power-Aware Routing in Mobile Ad Hoc Networks. Proc. International Conference on Mobile Computing and Networking, Dallas, TX, USA, 1998: 181-190.
[109] M. Maleki, K. Dantu, M. Pedram. Power-Aware Source Routing Protocol for Mobile Ad Hoc Networks. Proc. International Symposium on Low Power Electronics and Design, Monterey, CA, USA, 2002. Pages: 72-75.
[110] D. Kim, J. J. Garcia-Luna-Aceves, K. Obraczka, et al. Power-Aware Routing Based on the Energy Drain Rate for Mobile Ad Hoc Networks. Proc. 11th International Conference on Computer Communications and Networks, Miami, FL, USA, 2002. Pages: 565 -569.
[111] O. Goussevskaia, M. Machado, R. Mini, et al. Data Dissemination Based on the Energy Map. IEEE Communications Magazine, 2005, 43(7): 134-143.
[112] J. Wu, F. Dai, M. Gao, et al. On Calculating Power Aware Connected Dominating Sets for Efficient Routing in Ad Hoc Wireless Networks. IEEE/KICS Journal of Communications and Networks, 2002, 1(4): 59-70.
[113] R. Madan, S. Lall. Distributed Algorithms for Maximum Lifetime Routing in Wireless Sensor Networks. Proc. IEEE Global Telecommunications Conference, Dallas, TX, USA, 2004: 748-753.
[114] M. Pearlman, Z. Haas, P. Sholander, et al. Alternate Path Routing in Mobile Ad Hoc Networks. Proc.21st Century Military Communications Conference, Los Angeles, CA, USA, 2000: 501-506.
[115] M. Pearlman, Z. Haas, P. Sholander, et al. On the Impact of Alternate Path Routing for Load Balancing in Mobile Ad Hoc Networks. Proc. 1st Annual Workshop on Mobile and Ad Hoc Networking and Computing, Boston, MA, USA, 2000: 3-10.
[116] P. P. Pham, S. Perreau. Performance Analysis of Reactive Shortest Path and Multi-path Routing Mechanism with Load Balance. Proc. 22nd International Annual Joint Conference of the IEEE Computer and Communications Societies, San Francisco, CA, USA, 2003: 251-259.
[117] N. Jain, D. K. Madathil, D. P. Agrawal. Energy Aware Multi-path Routing for Uniform Resource Utilization in Sensor Networks. Proc. 2nd International Workshop on Information Processing in Sensor Networks, Palo Alto, CA, USA, 2003: 473-487.
[118] R. C. Shah, J. Rabaey. Energy Aware Routing for Low Energy Ad Hoc Sensor Networks. IEEE Wireless Communications and Networking Conference, Orlando, FL, 2002: 350-355.
[119] A. Tripathi, T. Ahmed, S. Pathak, et al. Paradigms for Mobile Agent Based Active Monitoring of Network Systems. Proc. 8th IEEE/IFIP Network Operations and Management Symposium, Florence, Italy, 2002: 65-78.
[120] G. Cabri, L. Leonardi, F. Zambonelli. Agents for Information Retrieval: Issues of Mobility and Coordination. Journal of Systems Architecture, 2000, 46(15): 1419-1433.
[121] G. Helmer, J. Wong, V. Honavar, et al. Intelligent Agents for Intrusion Detection. Proc. IEEE Information Technology Conference, Syracuse, NY, USA, 1998: pp. 121-124.
[122] T. Wang, S. Guan, T. Chan. Integrity Protection for Code-on-Demand Mobile Agents in E-commerce. Journal of System and Software, 2002, 60(3): 211-221.
[123] D. Milojicic. Agent Systems and Applications. IEEE Concurrency, 2000, 8(2): 222-231.
[124] [英]M．Wooldridge著，石纯一，张伟，徐晋晖，等译．多Agent系统引论．北京，电子工业出版社，2003
[125] D. Gavalas. Advanced Network Monitoring Application based on Mobile/Intelligent Agent Technology. Computer Communications, 2000, 23(8): 722-726.
[126] 朱淼良，邱瑜．移动代理系统综述．计算机研究与发展，2001，38(1)：16-25．
[127] D. M. Chess, C. G. Harrison, A. Kershenbaum. Mobile Agents: Are They a Good Idea. Technical Report, RC19887, IBM TJ Waston Research Center, 1995.
[128] D. B. Lange, M. Oshima. Seven Good Reasons for Mobile Agents. Communications of the ACM,1999, 42(3): 88-89.
[129] 张云勇，锦德．移动Agent技术．北京，清华大学出版社，2003．
[130] 吕玉海，徐学洲．移动Agent技术的发展．西安电子科技大学学报，2002，29(3)：392-397．
[131] L. Ismail, D. Hagimont. A Performance Evaluation of the Mobile Agent Paradigm. Proc. 14th Conference on Object-Oriented Programming, Systems, Languages, and Applications, Denver, CO, USA, 1999: 306-313.
[132] R. Jain. A Comparison of Mobile Agent and Client-Server Paradigms for Information Retrieval Tasks in Virtual Enterprises. Proc. Academia/Industry Working Conference on Research Challenges, Buffalo, NY, USA, 2000: 209-214.
[133] S. S. Iyengar, Q. Wu, N. S. V. Rao. Networking Paradigm for Distributed Sensor Networks. Proc. 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Lviv, Ukraine, 2003: 284-290.
[134] L. Tong, Q. Zhao, S. Adireddy. Sensor Networks with Mobile Agents. IEEE Military Communications Conference, Boston, MA, USA, 2003: 688-693.
[135] M. Ketel, N. Dogan, A. Homaifar. Distributed Sensor Networks Based on Mobile Agents Paradigm. Proc. 37th Southeastern Symposium on System Theory, Tuskegee, AL, USA, 2005: 411-414.
[136] FIPA. Foundation for Intelligent Physical Agents. http://www.fipa.org/repository/standardspecs.html.
[137] Object Management Group. The Mobile Agent System Interoperability Facility. http://www.omg.org/.
[138] 陶先平，吕建，马晓星，等．移动Agent系统基准模型的研究．电子学报，2002，30(12)：2119-2121．
[139] 冯新宇，陶先平，曹春，等．一种改进的移动Agent通信算法．计算机学报，2002，25(4)：357-364．
[140] 杨博，刘大有，杨鲲，等．移动Agent系统的主动通信机制．软件学报，2003，14(7)：1338-1344．
[141] 贾志勇，李振东，谢立．ACP：一种基于局部邮区的移动Agent通信算法．计算机研究与发展．2004，41(1)：47-52．
[142] 谭湘，顾毓清，包崇明．移动Agent系统安全性研究综述．计算机研究与发展，2003，40(7)：984-993．
[143] J. Zachary. Protecting Mobile Code in the World. IEEE Internet Computing, 2003, 7(2): 78-82.
[144] Q. Zhao, L. Tong. Quality-of-Service Specific Information Retrieval for Densely Deployed Sensor Networks. Proc. IEEE Military Communications Conference, Boston, MA, USA, 2003, pp. 591-596.
[145] M. Lotfinezhad, Ben Liang. Energy Efficient Clustering in Sensor Networks with Mobile Agents. IEEE Wireless Communications and Networking Conference, New Orleans, LA, USA, 2005, vol(3): 1872-1877.
[146] S. S. Iyengar, Q. Wu. Computational Aspects of Distributed Sensor Networks. Proc. 6th International Symposium on Parallel Architectures, Algorithms and Networks, Metro Manila, Philippines, 2002: 19-26.
[147] A. Boulis, C. Han, M. B. Srivastava. Design and Implementation of a Framework for Efficient and Programmable Sensor Networks. Proc. 1st International Conference on Mobile Systems, Applications, and Services, San Francisco, CA, USA, 2003: 187-200.
[148] L. Szumel, J. LeBrun, J. D. Owens. Towards a Mobile Agent Framework for Sensor Networks. Proc. 2nd IEEE Workshop on Embedded Networked Sensors, Sydney, Australia, 2005: 79-88.
[149] C.-L. Fok, G.-C. Roman, C. Lu. Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications. Proc. 24th IEEE International Conference on Distributed Computing Systems, Columbus, OH, USA, 2005: 653-662.
[150] Aglets. http://www.trl.ibm.com/aglets/.
[151] Voyager. http://www.recursionsw.com/mobile_agents.htm.
[152] Odyssey. http://www.genmagic.com/agents/odyssey.html.
[153] 李建枫，糜正琨，成际镇．NS-2移动代理网络仿真功能扩展设计和实现．系统仿真学报，2004，16(1)：85-90．
[154] K. Moizumi, G. Cybenko. The Travelling Agent Problem. Mathematics of Control, Signal and Systems, 1998, 14(3): 213-232.
[155] N. Migas, W. J. Buchanan, K. A. McAartney. Mobile Agents for Routing, Topology Discovery, and Automatic Network Reconfiguration in Ad-hoc Networks. Proc. 10th IEEE International Conference on Engineering of Computer-Based Systems, Huntsville, AL, USA, 2003: 200-206.
[156] S. Lu, C. Xu. A Formal Framework for Agent Itinerary Specification, Security Reasoning and Logic Analysis. Proc. 3rd International Workshop on Mobile Distributed Computing, Columbus, OH, USA, 2005: 580-586.
[157] I. C. Avramopoulos, M. E. Anagnostou. Optimal Component Configuration and Component Routing. IEEE Transactions on Mobile Computing, 2002, 1(4): 303-312.
[158] H. Qi, F. Wang. Optimal Itinerary Analysis for Mobile Agents in Ad Hoc Wireless Sensor Networks. Proc. 13th International Conference on Wireless Communications, Calgary, Canada, 2001: 147-153.
[159] A. Selamat, S. Omatu. Analysis on Route Selection by Mobile Agents Using Genetic Algorithm. Proc. SICE Annual Conference, Fukui, Japan, 2003: 2088-2093.
[160] A. Iqbal, J. Baumann, M. Straβer. Efficient Algorithms to Find Optimal Agent Migration Strategies. Technical Report, TR-1998-05, Stuttgart University, 1998.
[161] 刘大有，杨博，杨鲲，等．基于旅行图的移动Agent迁移策略．计算机研究与发展，2003，40(6)：838-845．
[162] 陈国良，王煦法等．遗传算法及其应用．北京，人民邮电出版社，1996．
[163] R. C. Eberhart, J. Kennedy. A New Optimizer Using Particle Swarm Theory. Proc. 6th International Symposium on Micromachine and Human Science, Nagoya, Japan, 1995: 39-43.
[164] J. Kennedy, R. C. Eberhart. Particle Swarm Optimization. Proc. IEEE International Conference on Neural Networks, Perth, Australia, 1995: 1942-1948.
[165] Y. Shi, R. C. Eberhart. Empirical Study of Particle Swarm Optimization. Proc. Congress on Evolutionary Computation, Piscataway, NJ, USA, 1999: 1945-1950.
[166] J. Kennedy, R. C. Eberhart. A Discrete Binary Version of the Particle Swarm Algorithm. Proc. IEEE International Conference on Systems, Man, and Cybernetics, Piscataway, NJ, USA, 1997: 4104-4109.
[167] Z. Wang, G. L. Durst, R. C. Eberhart, et al. Particle Swarm Optimization and Neural Network Application for Qsar. Proc. 3rd IEEE International Workshop on High Performance Computational Biology, Santa Fe, NM, USA, 2004.
[168] M. Clerc. Discrete Particle Swarm Optimization Illustrated by the Traveling Salesman Problem. 2000, http://clerc.maurice.free.fr/pso.
[169] P. Yuan, C. Ji, Y. Zhang etc al. Optimal Multicast Routing in Wireless Ad Hoc Sensor Networks. Proc. 2004 IEEE International Conference on Networking, Sensing and Control, Taipei, Taiwan, 2004: 367-371.
[170] H. Koskinen. Connectivity and Reliability in Ad Hoc Networks. M. S. Thesis, Department of Electrical and Communications Engineering, Helsinki University of Technology, Helsinki, Finland, 2003.
[171] Workshop on Collaborative Signal and Information Processing, chaired by F. Zhao, S. Kumar. Palo Alto, CA, USA, 2001, http://www.parc.xerox.com/cosense/csp.
[172] D. Li, K. Wong, Y.-H. Hu, et al. Detection, Classification and Tracking of Targets in Distributed Sensor Networks. IEEE Signal Processing Magazine, 2002, 19(2): 17-29.
[173] A. D'Costa, A. Sayeed. Collaborative Signal Processing for Distributed Classification in Sensor Networks. Proc. 2nd International Workshop on Information Processing in Sensor Networks, Palo Alto, CA, USA, 2003: 193-208.
[174] M. Duarte, Y.-H. Hu. Vehicle Classification in Distributed Sensor Networks. Journal of Parallel and Distributed Computing, 2004, 64(7): 826-838.
[175] A. D'Costa, V. Ramachandran, A. Sayeed. Distributed Classification of Gaussian Space-Time Sources in Wireless Sensor Networks. IEEE Journal of Selected Areas in Communications, 2004, 22(6): 1026-1036.
[176] J. Kotecha, V. Ramachandran, A. Sayeed. Distributed Multi-target Classification in Wireless Sensor Networks. IEEE Journal of Selected Areas in Communication, 2005, 23(4): 703-713.
[177] 王永庆．人工智能原理与方法．西安，西安交通大学出版社，1998．
[178] 何友，王国宏等．多传感器信息融合及应用．北京，电子工业出版社，2001．
② 严格说来，模拟(simulation)和仿真(emulation)是有区别的，但已在事实上长期相互混用。如无特别说明，本文不区分“模拟”和“仿真”，统一使用“仿真”一词，强调模拟系统过程的某些行为特征。
① 数据分组包(Packet)，又称包、分组或报文。
① Agent，国内尚未有统一翻译，可称为主体、代理或智能体等，这里保留不译。
① MAE，也有学者译为移动Agent服务设施，它与MAP含义相同，指移动Agent的运行支撑环境或平台。
[1] D. Estrin, R. Govindan, J. Heidemann, et al. Next Century Challenges: Scalable Coordination in Sensor Networks. Proc. 5th ACM/IEEE International Conference on Mobile Computing and Networking, Seattle, WA, USA, 1999: 263-270.
[2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, et al. Wireless Sensor Networks: A Survey. Computer Networks, 2002, 38: 393-422.
[3] S. Kumar, F. Zhao, D. Shepherd. Collaborative Signal and Information Processing in Microsensor Networks. IEEE Signal Processing Magazine, 2002, 19(2): 13-14.
[4] C. Y. Chong, S. Kumar. Sensor Networks Evolution, Opportunities, and Challenges. Proc. IEEE, 2003, 91(8): 1247-1256.
[5] 孙利民，李建中，陈渝，等．无线传感器网络．北京，清华大学出版社，2005．
[6] P. Coy, N. Gross. 21 Ideas for the 21st Century. Business Week Magazine, 1999, http://www.businessweek.com/1999/99_35/b3644024.htm.
[7] 10 Emerging Areas of Technology. MIT Technology Review Magazine, 2003, http://www.technologyreview.com.
[8] G. J. Pottie, W. J. Kaiser. Embedding the Internet: Wireless Integrated Network Sensors. Communications of the ACM, 2000, 43(5): 51-58.
[9] 王金龙，王呈贵，吴启辉，等．Ad Hoc移动无线网络．北京，国防工业出版社，2004．
[10] 郑少仁，王海涛，赵志峰，等．Ad Hoc网络技术．北京，人民邮电出版社，2005．
[11] R. Rashid, G. Robertson. Accent: A Communication Oriented Network Operating System Kernel. Proc. 8th Symposium on Operating System Principles, Pacific Grove, CA, USA, 1981: 64-75.
[12] R. Rashid, D. Julin, D. Orr, et. al. Mach: A System Software Kernel. Proc. 34th IEEE Computer Society International Conference, San Francisco, CA, USA, 1989: 176-178.
[13] C. Myers, A. Oppenheim, R. Davis, et. al. Knowledge Based Speech Analysis and Enhancement. Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, San Diego, CA, USA, 1984: 39-42.
[14] R. T. Lacoss. Distributed Mixed Sensor Aircraft Tracking. Proc. American Control Conference, Minneapolis, MN, USA, 1987: 1827-1830.
[15] D. Alberts, J. Garstka, F. Stein. Network Centric Warfare, 1999, http://www.dodccrp.org/publications/pdf/Alberts_NCW.pdf.
[16] WINS Project. http://www.janet.ucla.edu/WINS/.
[17] Smart Dust Project. http://robotics.eecs.berkeley.edu/～pister/SmartDust.
[18] NEST Project. http://webs.cs.berkeley.edu/nest-index.html.
[19] The Cooperative Engagement Capability. Johns Hopkins APL Technical Digest, 1995, 16(4): 377-396. http://techdigest.jhuapl.edu/td1604/APLteam.pdf.
[20] Y. Carts-Powell. Unattended Ground Sensors Stop and Analyze the Roses. OE Reports, 2000, http://www.spie.org/web/oer/april/apr00/cover2.html.
[21] D. Caterinicchia. DARPA Developing Killer Tech. FCW.COM, 2002. http://www.fcw.com/article76811.
[22] SensIT Project. http://www.sainc.com/sensit/.
[23] J. L. Paul. Smart Sensor Web: Web-based Exploitation of Sensor Fusion for Visualization of the Tactical Battlefield. IEEE Aerospace and Electronic Systems Magazine, 2001, 16(5): 29-36.
[24] ALERT System. http://www.altersystem.org/.
[25] Habitat Monitoring on Great Duck Island. http://www.greatduckisland.net.
[26] L. Schwiebert, S. Gupta, J. Weinmann. Research Challenges in Wireless Networks of Biomedical Sensors. Proc. 7th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Rome, Italy, 2001: 151-165.
[27] S. Meyer, A. Rakotonirainy. A Survey of Research on Context-Aware Homes. Proc. Australasian information security workshop conference on ACSW frontiers 2003, Adelaide, Astralia, 2003, 21: 159-168.
[28] AHRI Project. http://www.cc.gatech.edu/fce/ahri.
[29] NASA/JPL Sensor Webs Project. http://sensorwebs.jpl.nasa.gov/.
[30] CENS Project. http://research.cens.ucla.edu/.
[31] SensoNet Project. http://www.ece.gatech.edu/research/labs/bwn/Sensor/.
[32] Broadband & Wireless Networking Laboratory. http://www.ece.gatech.edu/research/labs/bwn/.
[33] COUGAR Project. http://www.cs.cornell.edu/database/cougar/index.htm.
[34] 任丰原，黄海宁，林闯．无线传感器网络．软件学报，2003，14(7)：1282-1291．
[35] 国家中长期科学和技术发展规划纲要(2006-2020)．http://www.gov.cn/jrzg/2006-02/09/content_183787.htm.
[36] 李建中，李金宝，石胜飞．传感器网络及其数据管理的概念，问题与进展．软件学报，2003，14(10)：1717-1727．
[37] 崔莉，鞠海玲，苗勇等．无线传感器网络研究进展．计算机研究与发展，2005，42(1)：163-174．
[38] 马祖长，孙怡宁，梅涛．无线传感器网络综述．通信学报，2004，25(4)：114-124．
[39] 徐雷鸣，庞博，赵耀．NS与网络模拟．北京，人民邮电出版社，2003．
[40] W. Ye, J. Heidemann, D. Estrin. An Energy-efficient Mac Protocol for Wireless Sensor Networks. Proc. 21th International Annual Joint Conference of the IEEE Computer and Communications Societies, New York, NY, USA, 2002: 1567-1576.
[41] W. Ye, J. Heidemann, D. Estrin. Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 2004, 12(3): 493-506.
[42] T. Van Dam, K. Langendoen. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 171-180.
[43] V. Rajendran, K. Obraczka, J. J. Garcia-Luna-Aceves. Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 181-192.
[44] C. C. Enz, A. El-Hoiydi, J.-D. Decotignie, et al. WiseNET: An Ultralow-Power Wireless Sensor Network Solution. IEEE Computer, 2004, 37(8): 62-70.
[45] J. Polastre, J. Hill, D. Culler. Versatile Low Power Media Access for Wireless Sensor Networks. Proc. 2nd ACM Conference on Embedded Networked Sensor Systems, Baltimore, MD, USA, 2004: 95-107.
[46] S. Hedetniemi, A. Liestman. A Survey of Gossiping and Broadcasting in Communication Networks. Networks, 1988, 18(4): 319-349.
[47] W. Heinzelman, A. Chandrakasan, H. Balakrishnan. Energy-Efficient Communication Protocol for Wireless Microsensor Networks. Proc. 33rd Annual Hawaii International Conference on System Sciences, Maui, Hawaii, USA, 2000: 4-7.
[48] K. Akkaya, M. Younis. A Survey on Routing Protocols for Wireless Sensor Networks. Ad Hoc Networks, 2005, 3(3): 325-349.
[49] J. Kulik, W. Rabiner, H. Balakrishnan. Adaptive Protocols for Information Dissemination in Wireless Sensor Networks. Proc. 5th ACM/IEEE Mobicom Conference, seattle, WA, USA, 1999: 174-185.
[50] C. Intanagonwiwat, R. Govinda, D. Estrin. Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks. Proc. 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Boston, MA, 2000: 56-67.
[51] C. Intanagonwiwat, R. Govinda, D. Estrin, et al. Directed Diffusion for Wireless Sensor Networking. IEEE/ACM Transactions on Networking, 2002, 11(1): 2-16.
[52] F. Silva, J. Heidemann, R. Govindan, et al. Directed Diffusion. Technical Report, ISI-TR-2004-586, USC/Information Sciences Institute, 2004.
[53] D. Niculescu. Positioning in Ad Hoc Sensor Networks. IEEE Network, 2004, 18(4): 24-29.
[54] I. Stojmenovic. Position Based Routing in Ad Hoc Networks. IEEE Communications Magazine, 2002, 40(7): 128-134.
[55] Y. Yu, R. Govindan, D. Estrin. Geographical and Energy-Aware Routing: A Recursive Data Dissemination Protocol for Wireless Sensor Networks. Technical Report, UCLA-CSD TR-01-0023, UCLA Computer Science Department, 2001.
[56] D. D. Clark, D. L. Tennenhouse. Architectural Considerations for a New Generation of Protocols. Proc. ACM Symposium on Communications Architectures and Protocols, Philadelphia, PA, USA, 1990: 200-208.
[57] M. B. Abbott, L. L. Peterson. Increasing Network Throughput by Integrating Protocol Layers. IEEE/ACM Transactions on Networking, 1993, 1(5): 600-610.
[58] Yu-Chee Tseng, Ten-Yueng Hsieh. Fully Power-Aware and Location-Aware Protocols for Wireless Multi-hop Ad Hoc Networks. Proc. 11th International Conference on Computer Communications and Networks, Miami, FL, USA 2002:608-613.
[59] R. Madan, S. Cui, S. Lall, et al. Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks. Proc. 24th International Annual Joint Conference of the IEEE Computer and Communications Societies, Miami, FL, USA, 2005: 1964-1975.
[60] D. Puccinelli, E. Sifakis, M. Haenggi. A Cross-Layer Approach to Energy Balancing in Wireless Sensor Networks. Proc. Workshop on Networked Embedded Sensing and Control, Notre Dame, IN, USA, 2005.
[61] M. L. Sichitiu. Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks. Proc. 23rd International Annual Joint Conference of the IEEE Computer and Communications Societies, HongKong, China, 2004: 1740-1750.
[62] L. P. Clare, E. H. Jennings, J. L. Ciao. Performance Evaluation Modeling of Networked Sensors. Proc. IEEE Aerospace Conference, Big Sky, Montana, USA, 2003: 1313-1322.
[63] J.-J. Lee, B. Krishnamachari, C.-C. J. Kuo. Impact of Heterogeneous Deployment on Lifetime Sensing Coverage in Sensor Networks. Proc. 1st IEEE Conference on Sensor and Ad Hoc Communications and Networks, Santa Clara, CA, USA, 2004: 367-376.
[64] A. Ghosh. Estimating Coverage Holes and Enhancing Coverage in Mixed Sensor Networks. Proc. 29th Annual IEEE International Conference on Local Computer Networks, Tampa, FL, USA, 2004: 68-76.
[65] Y. Zou, K. Chakrabarty. A Distributed Coverage- and Connectivity-Centric Technique for Selecting Active Nodes in Wireless Sensor Networks. IEEE Transactions on Computers, 2005, 54(8):978:991.
[66] T. Yan, T. He, J. A. Stankovic. Differentiated Surveillance for Sensor Networks. Proc. 1st ACM international conference on Embedded networked sensor systems, Los Angeles, CA, USA, 2003:51-62.
[67] C.-F. Huang, L.-C. Lo, Y.-C. Tseng, et al. Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks. Proc. IEEE International Symposium on Circuits and Systems, Kobe, Japan, 2005: 640-643.
[68] K. Barr, K. Asanovic. Energy Aware Lossless Data Compression. Proc. 1st International Conference on Mobile Systems, Applications and Services, San Francisco, CA, USA, 2003: 231-244.
[69] S. S. Pradhan, J. Kusuma, K. Ramchandran. Distributed Compression in a Dense Microsensor Network. IEEE Signal Processing Magazine, 2002, 19(2):51-60.
[70] J. Chou, D. Petrovic, K. Ramachandran. A Distributed and Adaptive Signal Processing Approach to Reducing Energy Consumption in Sensor Networks. Proc. 22nd International Annual Joint Conference of the IEEE Computer and Communications Societies, San Francisco, CA, USA, 2003:1054-1062.
[71] J. N. Laneman, G. W. Wornell. Distributed Space-Time-Coded Protocols for Exploiting Cooperative Diversity in Wireless Networks. IEEE Transactions on Information Theory, 2003, 49(10): 2415-2425.
[72] M. Haenggi. Twelve Reasons Not to Route over Many Short Hops. Proc. IEEE Vehicular Technology Conference, Los Angeles, CA, USA, 2004: 3130-3134.
[73] M. Haenggi. Analysis and Design of Diversity Schemes for Ad Hoc Wireless Networks. IEEE Journal on Selected Areas in Communications, 2003, 23(1):19-27.
[74] D. Petrovic, R. C. Shah, K. Ramchandran, et al. Data Funneling: Routing with Aggregation and Compression for Wireless Sensor Networks. Proc. 1st IEEE International Workshop on Sensor Network Protocols and Applications, Anchorage, AL, 2003: 156-162.
[75] T. Arici, B. Gedik, Y. Altunbasak, et al. PINCO: a Pipelined In-Network Compression Scheme for Data Collection in Wireless Sensor Networks. Proc. 12th International Conference on Computer Communications and Networks, Dallas, TX, USA, 2003: 539-544.
[76] S. J. Baek, G. de Veciana, Xun Su. Minimizing Energy Consumption in Large-scale Sensor Networks through Distributed Data Compression and Hierarchical Aggregation. IEEE Journal on Selected Areas in Communications, 2004, 22(6): 1130-1140.
[77] L. J. Guibas. Sensing, Tracking and Reasoning with Relations. IEEE Signal Processing Magazine, 2002, 19(2): 73-85.
[78] F. Zhao, J. Zhin, J. Reich. Information-Driven Dynamic Sensor Collaboration. IEEE Signal Processing Magazine. 2002, 19(2): 61-72.
[79] F. Zhao, J. Liu, J. Liu, et al. Collaborative Signal and Information Processing: an Information-Directed Approach. Proc. IEEE, 2003, 91(8): 1199-1209.
[80] H. Qi, S. Iyengar, K. Chakrabarty. Multiresolution Data Integration using Mobile Agents in Distributed Sensor Networks. IEEE Transactions on Systems, Man and Cybernetics, 2001, 31(3): 383-391.
[81] H. Qi, Y. Xu, X. Wang. Mobile-Agent-based Collaborative Signal and Information Processing in Sensor Networks. Proc. IEEE, 2003, 91(8): 1172-1183.
[82] Q. Wu, N. S. V. Rao, J. Barhen, et al. On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks. IEEE Transaction on Knowledge and Data Engineering, 2004, 16(6): 740-753.
[83] J. Liu, M. Chu, J. Reich, et al. State-Centric Programming for Sensor-Actuator Network Systems. IEEE Pervasive Computing, 2003, 2(4): 50-62.
[84] Opnet.http://www.opnet.com/.
[85] QualNet. http://www.scalable-networks.com/.
[86] OMNET++. http://www.omnetpp.org/index.php.
[87] NS-2. http://www.isi.edu/nsnam/dist/.
[88] Glomosim. http://pcl.cs.ucla.edu/projects/glomosim/.
[89] SensorSim. http://nesl.ee.ucla.edu/projects/sensorsim/.
[90] SENSIM. http://csc.lsu.edu/sensor_web/simulator.html.
[91] NRL SernsorSim. http://nrlsensorsim.pf.itd.nrl.navy.mil/.
[92] P. Levis, N. Lee, M. Welsh, et al. TOSSIM: Accurate and scalable simulation of entire TinyOS applications. Proc. 1st ACM Conference on Embedded Networked Sensor Systems, Los Angeles, CA, USA, 2003: 126-137.
[93] S. Chen. Routing Support for Providing Guaranteed End-to-End Quality-of-Service. Phd Thesis, University of Illino, 1999.
[94] T. S. Rappaport. Wireless Communications Principles and Practices, Second Edition. Beijing, Publishing House of Electronics Industry, 2004.
[95] E. S. Sousa, J. A. Silvester. Optimum Transmission Ranges in a Direct-Sequence Spread Spectrum Multihop Packet Radio Network. IEEE Journal on Selected Areas in Communications, 1990, 8(5): 762-771.
[96] P. Gupta, P. R. Kumar. The Capacity of Wireless Networks. IEEE Transactions on Information Theory, 2000, 46(2): 388-404.
[97] J.-H. Chang, L. Tassiulas. Energy Conserving Routing in Wireless Ad-hoc Networks. Proc. 19th International Annual Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel, 2000: 22-31.
[98] A. Shankar, Z. Liu. Maximum Lifetime Routing in Wireless Ad-hoc Networks. Proc. 23th International Annual Joint Conference of the IEEE Computer and Communications Societies, Hongkong, 2004, 12(4): 609-619.
[99] M. R. Pearlman, J. Deng, B. Liang, et al. Elective Participation in Ad Hoc Networks Based on Energy Consumption. Proc. IEEE Global Telecommunications Conference and Symposium on Ad-Hoc Wireless Networks, Taipei, Taiwan, 2002: 26-31.
[100] A. Sinhua, A. Chandrakasan. Dynamic Power Management in Wireless Sensor Network. IEEE Design and Test of Computer, 2001, 18(2): 62-74.
[101] C. LM, H. Kim, S. Ha. Dynamic Voltage Scheduling Technique for Low-power Multimedia Application Using Buffers. Proc. International Symposium on Low Power Electronics and Design. Huntington Beach , CA, USA, 2001: 34-39.
[102] V. Rodoplu, T. H. Meng. Minimum Energy Mobile Wireless Networks. IEEE Journal on Selected Areas in Communications, 1999, 17(8): 1333-1344.
[103] L. Li, JY Halpern. Minimum Energy Mobile Wireless Networks revisited. Proc. IEEE International Conference on Communications (ICC), Helsinki, Finland, 2001:278-283.
[104] J.-H. Chang, L. Tassiulas. Maximum Lifetime Routing in Wireless Sensor Networks. IEEE/ACM Transaction on Networking, 2004, 12(4): 609-619.
[105] M. Haenggi. Energy-Balancing Strategies for Wireless Sensor Networks. Proc. IEEE International Symposium on Circuits and Systems, Bangkok, Thailand, 2003:828-831.
[106] V. Rodoplu, T. H. Meng. Minimum Energy Mobile Wireless Networks. IEEE Journal on Selected Areas in Communications, 1999, 8(17): 1333-1344.
[107] C. Intanagonwiwat, D. Estrin, R. Govindan, et al. Impact of Network Density on Data Aggregation in Wireless Sensor Networks. Proc. 22nd International Conference on Distributed Computing Systems, Vienna, Austria, 2002: 457-458.
[108] S. Singh, M. Woo, C. S. Raghavendra. Power-Aware Routing in Mobile Ad Hoc Networks. Proc. International Conference on Mobile Computing and Networking, Dallas, TX, USA, 1998: 181-190.
[109] M. Maleki, K. Dantu, M. Pedram. Power-Aware Source Routing Protocol for Mobile Ad Hoc Networks. Proc. International Symposium on Low Power Electronics and Design, Monterey, CA, USA, 2002. Pages: 72-75.
[110] D. Kim, J. J. Garcia-Luna-Aceves, K. Obraczka, et al. Power-Aware Routing Based on the Energy Drain Rate for Mobile Ad Hoc Networks. Proc. 11th International Conference on Computer Communications and Networks, Miami, FL, USA, 2002. Pages: 565 -569.
[111] O. Goussevskaia, M. Machado, R. Mini, et al. Data Dissemination Based on the Energy Map. IEEE Communications Magazine, 2005, 43(7): 134-143.
[112] J. Wu, F. Dai, M. Gao, et al. On Calculating Power Aware Connected Dominating Sets for Efficient Routing in Ad Hoc Wireless Networks. IEEE/KICS Journal of Communications and Networks, 2002, 1(4): 59-70.
[113] R. Madan, S. Lall. Distributed Algorithms for Maximum Lifetime Routing in Wireless Sensor Networks. Proc. IEEE Global Telecommunications Conference, Dallas, TX, USA, 2004: 748-753.
[114] M. Pearlman, Z. Haas, P. Sholander, et al. Alternate Path Routing in Mobile Ad Hoc Networks. Proc.21st Century Military Communications Conference, Los Angeles, CA, USA, 2000: 501-506.
[115] M. Pearlman, Z. Haas, P. Sholander, et al. On the Impact of Alternate Path Routing for Load Balancing in Mobile Ad Hoc Networks. Proc. 1st Annual Workshop on Mobile and Ad Hoc Networking and Computing, Boston, MA, USA, 2000: 3-10.
[116] P. P. Pham, S. Perreau. Performance Analysis of Reactive Shortest Path and Multi-path Routing Mechanism with Load Balance. Proc. 22nd International Annual Joint Conference of the IEEE Computer and Communications Societies, San Francisco, CA, USA, 2003: 251-259.
[117] N. Jain, D. K. Madathil, D. P. Agrawal. Energy Aware Multi-path Routing for Uniform Resource Utilization in Sensor Networks. Proc. 2nd International Workshop on Information Processing in Sensor Networks, Palo Alto, CA, USA, 2003: 473-487.
[118] R. C. Shah, J. Rabaey. Energy Aware Routing for Low Energy Ad Hoc Sensor Networks. IEEE Wireless Communications and Networking Conference, Orlando, FL, 2002: 350-355.
[119] A. Tripathi, T. Ahmed, S. Pathak, et al. Paradigms for Mobile Agent Based Active Monitoring of Network Systems. Proc. 8th IEEE/IFIP Network Operations and Management Symposium, Florence, Italy, 2002: 65-78.
[120] G. Cabri, L. Leonardi, F. Zambonelli. Agents for Information Retrieval: Issues of Mobility and Coordination. Journal of Systems Architecture, 2000, 46(15): 1419-1433.
[121] G. Helmer, J. Wong, V. Honavar, et al. Intelligent Agents for Intrusion Detection. Proc. IEEE Information Technology Conference, Syracuse, NY, USA, 1998: pp. 121-124.
[122] T. Wang, S. Guan, T. Chan. Integrity Protection for Code-on-Demand Mobile Agents in E-commerce. Journal of System and Software, 2002, 60(3): 211-221.
[123] D. Milojicic. Agent Systems and Applications. IEEE Concurrency, 2000, 8(2): 222-231.
[124] [英]M．Wooldridge著，石纯一，张伟，徐晋晖，等译．多Agent系统引论．北京，电子工业出版社，2003
[125] D. Gavalas. Advanced Network Monitoring Application based on Mobile/Intelligent Agent Technology. Computer Communications, 2000, 23(8): 722-726.
[126] 朱淼良，邱瑜．移动代理系统综述．计算机研究与发展，2001，38(1)：16-25．
[127] D. M. Chess, C. G. Harrison, A. Kershenbaum. Mobile Agents: Are They a Good Idea. Technical Report, RC19887, IBM TJ Waston Research Center, 1995.
[128] D. B. Lange, M. Oshima. Seven Good Reasons for Mobile Agents. Communications of the ACM,1999, 42(3): 88-89.
[129] 张云勇，锦德．移动Agent技术．北京，清华大学出版社，2003．
[130] 吕玉海，徐学洲．移动Agent技术的发展．西安电子科技大学学报，2002，29(3)：392-397．
[131] L. Ismail, D. Hagimont. A Performance Evaluation of the Mobile Agent Paradigm. Proc. 14th Conference on Object-Oriented Programming, Systems, Languages, and Applications, Denver, CO, USA, 1999: 306-313.
[132] R. Jain. A Comparison of Mobile Agent and Client-Server Paradigms for Information Retrieval Tasks in Virtual Enterprises. Proc. Academia/Industry Working Conference on Research Challenges, Buffalo, NY, USA, 2000: 209-214.
[133] S. S. Iyengar, Q. Wu, N. S. V. Rao. Networking Paradigm for Distributed Sensor Networks. Proc. 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Lviv, Ukraine, 2003: 284-290.
[134] L. Tong, Q. Zhao, S. Adireddy. Sensor Networks with Mobile Agents. IEEE Military Communications Conference, Boston, MA, USA, 2003: 688-693.
[135] M. Ketel, N. Dogan, A. Homaifar. Distributed Sensor Networks Based on Mobile Agents Paradigm. Proc. 37th Southeastern Symposium on System Theory, Tuskegee, AL, USA, 2005: 411-414.
[136] FIPA. Foundation for Intelligent Physical Agents. http://www.fipa.org/repository/standardspecs.html.
[137] Object Management Group. The Mobile Agent System Interoperability Facility. http://www.omg.org/.
[138] 陶先平，吕建，马晓星，等．移动Agent系统基准模型的研究．电子学报，2002，30(12)：2119-2121．
[139] 冯新宇，陶先平，曹春，等．一种改进的移动Agent通信算法．计算机学报，2002，25(4)：357-364．
[140] 杨博，刘大有，杨鲲，等．移动Agent系统的主动通信机制．软件学报，2003，14(7)：1338-1344．
[141] 贾志勇，李振东，谢立．ACP：一种基于局部邮区的移动Agent通信算法．计算机研究与发展．2004，41(1)：47-52．
[142] 谭湘，顾毓清，包崇明．移动Agent系统安全性研究综述．计算机研究与发展，2003，40(7)：984-993．
[143] J. Zachary. Protecting Mobile Code in the World. IEEE Internet Computing, 2003, 7(2): 78-82.
[144] Q. Zhao, L. Tong. Quality-of-Service Specific Information Retrieval for Densely Deployed Sensor Networks. Proc. IEEE Military Communications Conference, Boston, MA, USA, 2003, pp. 591-596.
[145] M. Lotfinezhad, Ben Liang. Energy Efficient Clustering in Sensor Networks with Mobile Agents. IEEE Wireless Communications and Networking Conference, New Orleans, LA, USA, 2005, vol(3): 1872-1877.
[146] S. S. Iyengar, Q. Wu. Computational Aspects of Distributed Sensor Networks. Proc. 6th International Symposium on Parallel Architectures, Algorithms and Networks, Metro Manila, Philippines, 2002: 19-26.
[147] A. Boulis, C. Han, M. B. Srivastava. Design and Implementation of a Framework for Efficient and Programmable Sensor Networks. Proc. 1st International Conference on Mobile Systems, Applications, and Services, San Francisco, CA, USA, 2003: 187-200.
[148] L. Szumel, J. LeBrun, J. D. Owens. Towards a Mobile Agent Framework for Sensor Networks. Proc. 2nd IEEE Workshop on Embedded Networked Sensors, Sydney, Australia, 2005: 79-88.
[149] C.-L. Fok, G.-C. Roman, C. Lu. Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications. Proc. 24th IEEE International Conference on Distributed Computing Systems, Columbus, OH, USA, 2005: 653-662.
[150] Aglets. http://www.trl.ibm.com/aglets/.
[151] Voyager. http://www.recursionsw.com/mobile_agents.htm.
[152] Odyssey. http://www.genmagic.com/agents/odyssey.html.
[153] 李建枫，糜正琨，成际镇．NS-2移动代理网络仿真功能扩展设计和实现．系统仿真学报，2004，16(1)：85-90．
[154] K. Moizumi, G. Cybenko. The Travelling Agent Problem. Mathematics of Control, Signal and Systems, 1998, 14(3): 213-232.
[155] N. Migas, W. J. Buchanan, K. A. McAartney. Mobile Agents for Routing, Topology Discovery, and Automatic Network Reconfiguration in Ad-hoc Networks. Proc. 10th IEEE International Conference on Engineering of Computer-Based Systems, Huntsville, AL, USA, 2003: 200-206.
[156] S. Lu, C. Xu. A Formal Framework for Agent Itinerary Specification, Security Reasoning and Logic Analysis. Proc. 3rd International Workshop on Mobile Distributed Computing, Columbus, OH, USA, 2005: 580-586.
[157] I. C. Avramopoulos, M. E. Anagnostou. Optimal Component Configuration and Component Routing. IEEE Transactions on Mobile Computing, 2002, 1(4): 303-312.
[158] H. Qi, F. Wang. Optimal Itinerary Analysis for Mobile Agents in Ad Hoc Wireless Sensor Networks. Proc. 13th International Conference on Wireless Communications, Calgary, Canada, 2001: 147-153.
[159] A. Selamat, S. Omatu. Analysis on Route Selection by Mobile Agents Using Genetic Algorithm. Proc. SICE Annual Conference, Fukui, Japan, 2003: 2088-2093.
[160] A. Iqbal, J. Baumann, M. Straβer. Efficient Algorithms to Find Optimal Agent Migration Strategies. Technical Report, TR-1998-05, Stuttgart University, 1998.
[161] 刘大有，杨博，杨鲲，等．基于旅行图的移动Agent迁移策略．计算机研究与发展，2003，40(6)：838-845．
[162] 陈国良，王煦法等．遗传算法及其应用．北京，人民邮电出版社，1996．
[163] R. C. Eberhart, J. Kennedy. A New Optimizer Using Particle Swarm Theory. Proc. 6th International Symposium on Micromachine and Human Science, Nagoya, Japan, 1995: 39-43.
[164] J. Kennedy, R. C. Eberhart. Particle Swarm Optimization. Proc. IEEE International Conference on Neural Networks, Perth, Australia, 1995: 1942-1948.
[165] Y. Shi, R. C. Eberhart. Empirical Study of Particle Swarm Optimization. Proc. Congress on Evolutionary Computation, Piscataway, NJ, USA, 1999: 1945-1950.
[166] J. Kennedy, R. C. Eberhart. A Discrete Binary Version of the Particle Swarm Algorithm. Proc. IEEE International Conference on Systems, Man, and Cybernetics, Piscataway, NJ, USA, 1997: 4104-4109.
[167] Z. Wang, G. L. Durst, R. C. Eberhart, et al. Particle Swarm Optimization and Neural Network Application for Qsar. Proc. 3rd IEEE International Workshop on High Performance Computational Biology, Santa Fe, NM, USA, 2004.
[168] M. Clerc. Discrete Particle Swarm Optimization Illustrated by the Traveling Salesman Problem. 2000, http://clerc.maurice.free.fr/pso.
[169] P. Yuan, C. Ji, Y. Zhang etc al. Optimal Multicast Routing in Wireless Ad Hoc Sensor Networks. Proc. 2004 IEEE International Conference on Networking, Sensing and Control, Taipei, Taiwan, 2004: 367-371.
[170] H. Koskinen. Connectivity and Reliability in Ad Hoc Networks. M. S. Thesis, Department of Electrical and Communications Engineering, Helsinki University of Technology, Helsinki, Finland, 2003.
[171] Workshop on Collaborative Signal and Information Processing, chaired by F. Zhao, S. Kumar. Palo Alto, CA, USA, 2001, http://www.parc.xerox.com/cosense/csp.
[172] D. Li, K. Wong, Y.-H. Hu, et al. Detection, Classification and Tracking of Targets in Distributed Sensor Networks. IEEE Signal Processing Magazine, 2002, 19(2): 17-29.
[173] A. D'Costa, A. Sayeed. Collaborative Signal Processing for Distributed Classification in Sensor Networks. Proc. 2nd International Workshop on Information Processing in Sensor Networks, Palo Alto, CA, USA, 2003: 193-208.
[174] M. Duarte, Y.-H. Hu. Vehicle Classification in Distributed Sensor Networks. Journal of Parallel and Distributed Computing, 2004, 64(7): 826-838.
[175] A. D'Costa, V. Ramachandran, A. Sayeed. Distributed Classification of Gaussian Space-Time Sources in Wireless Sensor Networks. IEEE Journal of Selected Areas in Communications, 2004, 22(6): 1026-1036.
[176] J. Kotecha, V. Ramachandran, A. Sayeed. Distributed Multi-target Classification in Wireless Sensor Networks. IEEE Journal of Selected Areas in Communication, 2005, 23(4): 703-713.
[177] 王永庆．人工智能原理与方法．西安，西安交通大学出版社，1998．
[178] 何友，王国宏等．多传感器信息融合及应用．北京，电子工业出版社，2001．