面向应用的移动密集网络信息收集研究
|
摘要
伴随着信息技术的发展,无线传感网络日益成为研究的热点,而信息收集和目标跟踪均是无线传感网络应用的关键技术。针对大规模移动无线传感网络数据收集中消息复杂度过高的问题,以移动目标跟踪为主要应用背景,我们开发了基于人的行为特征移动成簇算法(BMC)和基于概率的多簇快速信息统计算法(PCFD)。上述算法已成功的应用于“基于CNGI和WSN的矿山井下定位与应急联动系统”。
在实际环境中,信号干扰将使节点在簇成员和独立节点间频繁的抖动,从而大大增加了成簇算法的消息复杂度。为解决该问题,我们设计了延迟保证的信号平滑机制(DBSS)和双阈值成簇机制(DTC)。我们还对信号平滑算法的参数选择问题进行了详细的理论分析。优化参数后的DBSS信号平滑算法可以去除信号中90%的波动,并削弱剩余毛刺50%的强度。DTC利用双阈值线来限制节点的加入和离开簇,阈值可根据系统需求调节。其可以有效的稳定成簇算法,进一步减小消息复杂度。
在传统的跟踪系统中,移动节点周期性的发送定位信息包。随着移动节点数目的增加,这些方法将导致较高的丢包率,并缩短网络的生命周期。在实际应用中,我们发现很多移动节点彼此极为接近,以至于定位算法的精度无法区分,因此通过信息融合可以减少系统的消息负载。针对基于射频(RF)的人员跟踪系统,通过采用接收信号强度(RSSI),本文提出基于人的移动特征的成簇算法,根据移动节点间的距离进行成簇,并可以有效地维护簇。在BMC中,簇头代替了每个节点周期性地向网络发送定位信息包,因此极大的减小了消息复杂度。在簇维护中,我们设计了基于概率的状态通告机制(PSI),其可以高效地对簇进行维护。模拟显示基于BMC(采用了DBSS和DTC)的定位信息收集较传统的方法(TPTS)消息复杂度减小了64%。
为快速高效的收集大规模移动网络中的信息,我们开发了基于概率的多簇快速信息统计算法。PCFD以概率的方法选举簇头,然后各簇头分别统计本簇内的消息,然后发送至网络。不但有效的控制了簇头数量,并可以根据信息相似度来组成簇,最大化消息融合度。实验及理论分析证明,该算法的消息复杂度可达O(M+n),其中M为网络节点数,n为簇头数量。
本文的主要贡献和创新点如下:
1.提出了基于权值和双曲线的信号平滑处理算法DBSS,并对其各参数选择进行了理论分析与优化。
2.借鉴人的行为特征,设计了适用于人员跟踪的定位信息收集算法BMC,并提出了基于概率的状态通告机制PSI对簇进行高效的维护。
3.开发了基于概率成簇的快速高效的节点信息收集算法PCFD。
4.基于本文算法和理论在Micaz上开发实现了基于CNGI和WSN的矿山井下定位与应急联动系统。该项目为国家发改委下一代互联网重大专项。
With the development of information technology, Wireless Sensor Network is increasingly focused. Both of data gathering and tracking are the key application of Wireless Sensor Network. Aiming at the problem of high message complexity in data gathering of the large scale mobile Wireless Sensor Network, taking tracking as our main applications, we develop human-Behavior based Mobile Clustering Mechanism (BMC) and Probability-based multi-Cluster for Fast Data gathering (PCFD) for large-scale mobile network. The above algorithms are successfully applied in the pro-ject“CNGI and WSN Based Mine Underground Localization and Integrated Emer-gency Response System”.
Signal interference will wobble the clusters in practical environment, so it de-grades the performance of the clustering algorithm dramatically. To resolve the issue, Delay-ensured Best-effort Signal Smoothness (DBSS) and Dual Threshold Clustering (DTC) are developed. We also theoretically analyze the selection rules of the smoothness parameters. With the optimized parameters, DBSS smoothes out more than 90% of the fluctuations and the stubborn ones left are also weakened by about 50%. DTC adopts two thresholds lines to guard joining and leaving of a cluster. The thresholds can be adjusted according to the requirement of the system. It can reduce the message complexity greatly, thereby stabilizing the clustering algorithm.
In traditional tracking systems, the mobiles report their locations periodically. With the number of the mobiles increasing, these methods will result in high loss rate of packets and rapid depletion of the network energy. In practice, we observe that some mobiles are so close to each other that we are informed the same location from the localization algorithm. So it is necessary and possible to reduce message complex-ity through merging the location messages. By exploiting the Received Signal Strength Indicator (RSSI), this paper proposes a human-Behavior based Mobile Clus-tering Mechanism for Radio Frequency (RF)-based Person Tracking Systems. It con-structs clusters according to the distance between mobiles and maintains clusters effi-ciently. In BMC, only the cluster-heads report locations periodically instead of each node, thus the message complexity is reduced greatly. In the cluster maintenance stage, we devise the named Probability-based State Informing mechanism (PSI), which can maintain the clusters effectively. The simulation shows that BMC based location re- port outperforms traditional ones by 64% of message reduction on average in impar-tial testing scenes.
To gathering the data quickly and effectively in large-scale mobile Wireless Sensor Network, we develop Probability-based multi-Cluster for Fast Data gathering. PCFD selects cluster head with a variable probability. Then every cluster collects its own message and sends to the network. This method can not only control the number of clusters though adjusting the probability is that, but also construct the clusters ac-cording to the interests. Both simulation and theoretical analysis prove that the mes-sage complexity is O(M+n), where M is the scale of the network and n is the number of clusters.
The contributions of this dissertation are listed as follows:
1. We propose a signal smoothness algorithm DBSS, which is based on weighted means and dual curves. Also we analyze and optimize the selection rules of DBSS.
2. Exploiting the traits of human behavior, we design a location data gathering algo-rithm for person tracking and the probability based state informing mechanism (PSI) is devised to maintain the cluster effectively.
3. The probability based clustering algorithm PCFD is proposed to gathering the nodes’information quickly and effectively.
4. Based on the algorithm and theory proposed in this dissertation, we develop and implement the CNGI and WSN Based Mine Underground Localization and Inte-grated Emergency Response System on the Micaz platform. The project is China the Next Generation Internet Project Important Special Item from the State De-velopment and Reform Commission of China.
在实际环境中,信号干扰将使节点在簇成员和独立节点间频繁的抖动,从而大大增加了成簇算法的消息复杂度。为解决该问题,我们设计了延迟保证的信号平滑机制(DBSS)和双阈值成簇机制(DTC)。我们还对信号平滑算法的参数选择问题进行了详细的理论分析。优化参数后的DBSS信号平滑算法可以去除信号中90%的波动,并削弱剩余毛刺50%的强度。DTC利用双阈值线来限制节点的加入和离开簇,阈值可根据系统需求调节。其可以有效的稳定成簇算法,进一步减小消息复杂度。
在传统的跟踪系统中,移动节点周期性的发送定位信息包。随着移动节点数目的增加,这些方法将导致较高的丢包率,并缩短网络的生命周期。在实际应用中,我们发现很多移动节点彼此极为接近,以至于定位算法的精度无法区分,因此通过信息融合可以减少系统的消息负载。针对基于射频(RF)的人员跟踪系统,通过采用接收信号强度(RSSI),本文提出基于人的移动特征的成簇算法,根据移动节点间的距离进行成簇,并可以有效地维护簇。在BMC中,簇头代替了每个节点周期性地向网络发送定位信息包,因此极大的减小了消息复杂度。在簇维护中,我们设计了基于概率的状态通告机制(PSI),其可以高效地对簇进行维护。模拟显示基于BMC(采用了DBSS和DTC)的定位信息收集较传统的方法(TPTS)消息复杂度减小了64%。
为快速高效的收集大规模移动网络中的信息,我们开发了基于概率的多簇快速信息统计算法。PCFD以概率的方法选举簇头,然后各簇头分别统计本簇内的消息,然后发送至网络。不但有效的控制了簇头数量,并可以根据信息相似度来组成簇,最大化消息融合度。实验及理论分析证明,该算法的消息复杂度可达O(M+n),其中M为网络节点数,n为簇头数量。
本文的主要贡献和创新点如下:
1.提出了基于权值和双曲线的信号平滑处理算法DBSS,并对其各参数选择进行了理论分析与优化。
2.借鉴人的行为特征,设计了适用于人员跟踪的定位信息收集算法BMC,并提出了基于概率的状态通告机制PSI对簇进行高效的维护。
3.开发了基于概率成簇的快速高效的节点信息收集算法PCFD。
4.基于本文算法和理论在Micaz上开发实现了基于CNGI和WSN的矿山井下定位与应急联动系统。该项目为国家发改委下一代互联网重大专项。
With the development of information technology, Wireless Sensor Network is increasingly focused. Both of data gathering and tracking are the key application of Wireless Sensor Network. Aiming at the problem of high message complexity in data gathering of the large scale mobile Wireless Sensor Network, taking tracking as our main applications, we develop human-Behavior based Mobile Clustering Mechanism (BMC) and Probability-based multi-Cluster for Fast Data gathering (PCFD) for large-scale mobile network. The above algorithms are successfully applied in the pro-ject“CNGI and WSN Based Mine Underground Localization and Integrated Emer-gency Response System”.
Signal interference will wobble the clusters in practical environment, so it de-grades the performance of the clustering algorithm dramatically. To resolve the issue, Delay-ensured Best-effort Signal Smoothness (DBSS) and Dual Threshold Clustering (DTC) are developed. We also theoretically analyze the selection rules of the smoothness parameters. With the optimized parameters, DBSS smoothes out more than 90% of the fluctuations and the stubborn ones left are also weakened by about 50%. DTC adopts two thresholds lines to guard joining and leaving of a cluster. The thresholds can be adjusted according to the requirement of the system. It can reduce the message complexity greatly, thereby stabilizing the clustering algorithm.
In traditional tracking systems, the mobiles report their locations periodically. With the number of the mobiles increasing, these methods will result in high loss rate of packets and rapid depletion of the network energy. In practice, we observe that some mobiles are so close to each other that we are informed the same location from the localization algorithm. So it is necessary and possible to reduce message complex-ity through merging the location messages. By exploiting the Received Signal Strength Indicator (RSSI), this paper proposes a human-Behavior based Mobile Clus-tering Mechanism for Radio Frequency (RF)-based Person Tracking Systems. It con-structs clusters according to the distance between mobiles and maintains clusters effi-ciently. In BMC, only the cluster-heads report locations periodically instead of each node, thus the message complexity is reduced greatly. In the cluster maintenance stage, we devise the named Probability-based State Informing mechanism (PSI), which can maintain the clusters effectively. The simulation shows that BMC based location re- port outperforms traditional ones by 64% of message reduction on average in impar-tial testing scenes.
To gathering the data quickly and effectively in large-scale mobile Wireless Sensor Network, we develop Probability-based multi-Cluster for Fast Data gathering. PCFD selects cluster head with a variable probability. Then every cluster collects its own message and sends to the network. This method can not only control the number of clusters though adjusting the probability is that, but also construct the clusters ac-cording to the interests. Both simulation and theoretical analysis prove that the mes-sage complexity is O(M+n), where M is the scale of the network and n is the number of clusters.
The contributions of this dissertation are listed as follows:
1. We propose a signal smoothness algorithm DBSS, which is based on weighted means and dual curves. Also we analyze and optimize the selection rules of DBSS.
2. Exploiting the traits of human behavior, we design a location data gathering algo-rithm for person tracking and the probability based state informing mechanism (PSI) is devised to maintain the cluster effectively.
3. The probability based clustering algorithm PCFD is proposed to gathering the nodes’information quickly and effectively.
4. Based on the algorithm and theory proposed in this dissertation, we develop and implement the CNGI and WSN Based Mine Underground Localization and Inte-grated Emergency Response System on the Micaz platform. The project is China the Next Generation Internet Project Important Special Item from the State De-velopment and Reform Commission of China.
引文
[1].任丰原,黄海宁,林闯.无线传感器网络〔J〕.软件学报.2003,14(7):1282-1291.
[2].曾鹏,于海斌,梁英等. (J)信息与控制.2004,分布式无线传感器网络体系结构及应用支撑技术研究33(3):307一313.
[3].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(J).软件学报.2003,14(10):1717一1727.
[4].马祖长,孙怡宁,梅涛.无线传感器网络综述〔J〕.通信学报.2004,25(4): 114一124.
[5].A. Y. Wang, S. H. Cho, C. G. Sodini, and A. P. Chandrakasan. Energy Efficient Modulation and MAC for Asymmetric RF Microsensor ystems. In Intl. Symp. on Low Power Electronics and Design (ISLPED’01), pages 96–99, August 2001.
[6].C. Savarese, J. M. Rabaey, and J. Beutel. Locationing in Distributed Ad-Hoc Wireless Sensor Networks. In Proc. Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2001), Salt Lake City, Utah, May 2001.
[7].R.X. Gao and P. Hunerberg. CDMA-based wireless data transmitter for embedded sensors. In Proc. 18th IEEE Instrumentation and Measurement Technology Conf., volume 3, pages 1778–1783, 2001.
[8].E. Shih, S.-H. Cho, N. Ickes, R. Min, A. Sinha, A. Wang, and A. Chandrakasan. Physi-cal-Layer Driven Protocol and Algorithm Design for Energy-Efficient Wireless Sensor Net-works. In Proc 7th Ann. Intl. Conf. onMobile Computing and Networking, pages 272–286, Rome, Italy, July 2001. ACM.
[9].L. Charlie Zhong, R. C. Shah, C. Guo, and J. M. Rabaey. An Ultra-Low Power and Distrib-uted Access Protocol for Broadband Wireless Sensor Networks. In IEEE Broadband Wire-less Summit, Las Vegas, NV, May 2001.
[10].W. Ye, J. Heidemann, and D. Estrin. An energy-efficient MAC protocol for wireless sensor networks. In Proc. IEEE Infocom, 2002.
[11].K. Sohrabi, J. Gao, V. Ailawadhi, and G. J. Pottie. Protocols for self-organization of a wire-less sensor network. IEEE Personal Communications, 7(5):16–27, 2000.
[12].C. Schurgers, V. Tsiatsis, S. Ganeriwal, and M. B. Srivastava. Optimizing Sensor Networks in the Energy-Latency-Density Design Space. IEEE Transactions on Mobile Computing, 1(1), 2002.
[13].Y. Sankarasubramaniam, I.F. Akyildiz, and S.W.McLaughlin. Energy Efficiency Based Packet Size Optimization in Wireless Sensor Networks. In Proc. 1st IEEE Intl. Workshop onSensor Network Protocols and Applications (SNPA), Anchorage, AK, May 2003.
[14].M. Zorzi and R. R. Rao. Error Control and Energy Consumption in Communications for Nomadic Computing. IEEE Trans. on Computers, 46(3):279–289, 1997.
[15].E. Shih, B. Calhoun, S.-H. Cho, and A. Chandrakasan. Energy-Efficient Link Layer for Wireless Microsensor Networks. In Proc. Workshop on VLSI 2001 (WVLSI’01), April 2001.
[16].J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan. Build-ing Efficient Wireless Sensor Networks with Low-Level Naming. In Proc. Symp. on Operat-ing System Principles (SOSP 2001), pages 146–159, Lake Louise, Banff, Canada, October 2001.
[17].C. Schurgers, G. Kulkarni, and M. B. Srivastava. Distributed Assignment of Encoded MAC Addresses in Sensor Networks. In Proc. Symposium on Mobile Ad Hoc Networking & Computing (MobiHoc’01), Long Beach, CA, October 2001.
[18].W. Adjie-Winoto, E. Schwartz, H. Balakrishnan, and J. Lilley. The Design and Implementa-tion of an Intentional Naming System. In Proc. of the 7th ACM Symp. on Operating Systems Principles, pages 186–201. ACM Press, 1999.
[19].T. Berners-Lee, J. Hendler, and O. Lassila. The Semantic Web. Scientific American, May 2001. http://www.scientificamerican.com.
[20].A. Carzaniga and A. L. Wolf. Content-based Networking: A New Communication Infra-structure. In NSF Workshop on an Infrastructure for Mobile and Wireless Systems, Scotts-dale, Arizona, October 2001.
[21].W. R. Heinzelman, J. Kulik, and H. Balakrishnan. Adaptive Protocols for Information Dis-semination in Wireless Sensor Networks. In Proc. 5th Ann. Intl. Conf. on Mobile Computing and Networking, pages 174–185, Seattle, WA, August 2001. ACM. http://citeseer.nj.nec.
[22].J. Elson and K. Romer. Wireless sensor networks: a new regime for time synchronization. ACM SIGCOMM Computer Communication Review, 33(1):149–154, 2003.
[23].K. Romer. Time Synchronization in Ad Hoc Networks. In Proc. 2nd ACM Intl. Symp on Mobile Ad Hoc Networking and Computing, (MobiHoc), Long Beach, CA, 2001.
[24].J. van Greunen and J. Rabaey. Lightweight Time Synchronization for Sensor Networks. In Proc. 2nd ACM Intl. Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[25].W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In Proc. 33rd Hawaii Intl. Conf. on System Sciences, January 2000. http://www-mtl.mit.edu/?wendi/leach/hicss00.html
[26].S. Basagni, D. Turgut, and S. K. Das. Mobility-Adaptive Protocols for Managing Large Ad Hoc Networks. In Proc. of the IEEE Intl. Conf. on Communications (ICC), Helsinki, Finland, June 2001.
[27].T. J. Kwon andM. Gerla. Efficient flooding with Passive Clustering (PC) in ad hoc networks. ACM SIGCOMM Computer Communication Review, 32(1):44–56, 2002.
[28].P. Gupta and P. R. Kumar. Critical Power for Asymptotic Connectivity in Wireless Networks. In W.M. McEneany, G. Yin, and Q. Zhang, editors, Stochastic Analysis, Control, Optimiza-tion and Applications, pages 547–566. Birkhauser, Boston, 1998. http://black.csl.uiuc.edu/ prkumar/ps_files/connectivity.ps.
[29].M. Kubisch, H. Karl, A.Wolisz, L. C. Zhong, and J. Rabaey. Distributed Algorithms for Transmission Power Control in Wireless Sensor Networks. In Proc. IEEE Wireless Commu-nications and Networking Conference (WCNC), New Orleans, LA, March 2003.
[30].J. P. Monks, J.-P. Ebert, A. Wolisz, and W. W. Hwu. A Study of the Energy Saving and Ca-pacity Improvement Potential of Power Control in Multi-hop Wireless Networks. In Proc. of Workshop on Wireless Local Networks, Tampa, Florida, USA, November 2001. Held in conjunction with Conf. of Local Computer Networks (LCN).
[31].R. Ramanathan and R. Rosales-Hain. Topology Control of Multihop Wireless Networks us-ing Transmit Power Adjustement. In Proc. IEEE Infocom, Tel-Aviv, Israel, March 2000. http: //www.ieee-infocom.org/2000/papers/538.ps.
[32].P. Santi and D. M. Blough. The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks. IEEE Trans. on Mobile Computing, 2:25–39, March 2003.
[33].A. Safwat, H. Hassanein, and H. Mouftah. A MAC-based Performance Study of En-ergy-Aware Routing Schemes in Wireless Ad hoc Networks. In Proc. IEEE Globecom, 2002.
[34].R. Kannan, S. Sarangi, S. S. Iyengar, and L. Ray. Sensor-Centric Quality of Routing in Sen-sor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[35].J. Cartigny, D. Simplot, and I. Stojmenovic. Localized minimum-energy broadcasting in ad-hoc networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[36].A. K. Das, R. J. Marks, M. El-Sharkawi, P. Arabshabi, and A. Gray. Minimum Power Broadcast Trees for Wireless Networks: Integer Programming Formulations. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[37].C. Florens and R. McEliece. Packets Distribution Algorithms for Sensor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[38].W. Liang. Constructing Minimum -Energy Broadcast Trees in Wireless Ad Hoc Networks. In Proc. 3rd ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MobiHoc),Lausanne, Switzerland, 2002.
[39].J. Luo, P. Th. Eugster, and J.-P. Hubaux. Route Driven Gossip: Probabilistic Relibale Multi-cast in Ad Hoc Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[40].J. E. Wieselthier, G. D. Nguyen, and A. Ephremides. On the Construction of Energy-Efficient Broadcast and Multicast Trees in Wireless Networks. In Proc. IEEE Infocom, Tel-Aviv, Is-rael, March 2000.
[41].R. Cristescu and M. Vetterli. Power Efficient Gathering of Correlated Data: Optimization, NP-Completeness and Heuristics. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Net-working and Computing (MobiHoc), Annapolis, MD, 2003.
[42].S. Lindsey and K. M. Sivalingam. Data gathering algorithms in sensor networks using energy metrics. IEEE Trans. on Parallel and Distributed Systems, 13(9):924–934, 2002.
[43].F. Kuhn, R. Wattenhofer, and A. Zollinger. Worst-Case Optimal and Average-Case Efficient Geometric Ad-Hoc Routing. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MobiHoc), Annapolis, MD, 2003.
[44].M.Mauve, J.Widmer, and H. Hartenstein. A Survey on Position-Based Routing in Mobile Ad-Hoc Networks. IEEE Network, November 2001.
[45].Y. Xu, J. Heidemann, and D. Estrin. Geography-Informed Energy Conservation for Ad Hoc Routing. In Proc. 7th Ann. Intl. Conf. on Mobile Computing and Networking, pages 70–84, Rome, Italy, July 2001. ACM.
[46].P. Th. Eugster, P. A. Felber, R. Guerraoui, and A.-M. Kermarrec. The many faces of pub-lish/subscribe. ACM Computing Surveys (CSUR), 35(2):114–131, 2003.
[47].C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva. Directed Diffusion for Wireless Sensor Networking. IEEE Trans. on Networking, February 2003.
[48].J. Liu, F. Zhao, and D. Petrovic. Information-Directed Routing in Ad Hoc Sensor Networks. In Proc. 2nd ACM Intl.Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[49].S. Ratnasamy, P. Francis, M. Handley, R. Karp, and S. Shenker. A Scalable Con-tent-Addressable Network. In Proc. ACM SIGCOMM, 2001.
[50].Z. Fu, P. Zerfos, H. Luo, S. Lu, L. Zhang, andM. Gerla. The Impact of Multihop Wireless Channel on TCP Throughput and Loss. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[51].S.-J. Park and R. Sivakumar. Sink-to-Sensors Reliability in Sensor Networks. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MOBIHOC), Annapolis, MD, June 2003.
[52].Y. Sankarasubramaniam, O.B. Akan, and I.F. Akyildiz. ESRT: Event-to-Sink Reliable Transport in Wireless Sensor Networks. In Proc. ACM MOBIHOC 2003, Annapolis, Mary-land, USA, June 2003. ACM Press.
[53].F. Stann and J. Heideman. RMST: Reliable Data Transport in Sensor Networks. In Proc. 1st IEEE Intl.Workshop on Sensor Network Protocols and Applications (SNPA), Anchorage, AK,May 2003.
[54].C.-Y. Wan, A. T. Campbell, and L. Krishnamurthy. PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks. In Proc. 1st ACM Intl. Workshop on Sensor Networks and Ap-plications (WSNA), Atlanta, GA, September 2002.
[55].R. Want, A. Hopper, V. Falcao, and J. Gibbons,“The Active Badge Location System,”ACM Trans. Inf. Syst., vol. 10, no. 1, pp. 91–102, 1992;
[56].N. B. Priyantha, A. Chakraborty, and H. Balakri-shnan,“The Cricket location-support sys-tem,”in MobiCom’00: Proceedings of the 6th annual international conference on Mobile computing and networking. New York, NY, USA: ACM Press, 2000, pp. 32–43;
[57].P. Bahl and V. N. Padmanabhan,“RADAR: An In-Building RF-Based User Location and Tracking System.”in Proceedings of the IEEE INFOCOM 2000, 2000, pp. 775–784;
[58].Cisco System,“Data Sheet for Cisco Wireless Location Appliance,”Cisco Inc, Tech. Rep., 2005;
[59].Pete Steggles and Stephan Gschwind,“The Ubisense Smart Space Platform,”Ubisense Limited, Tech. Rep., May 2005;
[60].Yui-Wah Lee, Erich Stuntebeck, and Scott C. Miller,“MERIT: Mesh of RF Sensors for Indoor Tracking”, Secon’06, 2006;
[61].L.M. Ni, Y. Liu, Y.C. Lau, and A.P. Patil,“LANDMARC: Indoor Location Sensing Using Active RFID,”Wireless Networks, vol. 10, pp. 701–710, 2004;
[62].West, D., Introduction to Graph Theory, Second edition, Prentice Hall, Upper Saddle River, N.J., (2001)
[63].Chen, Y., P., Liestman, A. L., Approximating Minimum Size Weakly-Connected Dominating Sets for Clustering Mobile Ad Hoc Networks, 3rd ACM International Symposium on Mobile Ad Hoc Networks and Computing,(2002), pp. 165-72.
[64].Haynes, T., W., Hedetniemi, S., T., Slater, P., J., Domination in graphs, Advanced Topics, Marcel Dekker,Inc.,(1998).
[65].Baker, D., Ephremides, A., The Architectural Organization of a Mobile Radio Network via a Distributed Algorithm, Communications, IEEE Transactions, vol. 29-11, (1981), pp. 1694-1701.
[66].Gerla, M, Tsai, J. T., Multicluster, mobile, multimedia radio network, Wireless Networks, vol. 1(3), (1995),pp. 255-265.
[67].Chen, Y. P., Liestman, A.L., A Zonal Algorithm for Clustering Ad Hoc Networks, Interna-tional Journal of Foundations of Computer Science, vol. 14(2), (2003), pp. 305-322.
[68].Guha, S., Khuller, S., Approximation Algorithms for Connected Dominating Sets, Springer-Verlag New York,(1998), LLC, ISSN: 0178-4617.
[69].Stojmenovic, I., Seddigh, M., Zunic, J. Dominating sets and neighbor elimination-based broadcasting algorithms in wireless networks, IEEE Transactions on Parallel and Distributed Systems, (2002), pp. 14-25.
[70].C.-C. Chiang et al.,“Routing in Clustered Multihop, Mobile Wireless Networks with Fading Channel,”in Proc. IEEE SICON’97, 1997.
[71].A. Ephremides, J. E. Wieselthier, and D. J. Baker,“A Design Concept for Reliable Mobile Radio Networks with Frequency Hopping Signaling,”in Proc. IEEE, vol. 75, 1987, pp. 56–73.
[72].M. Gerla and J. T. Tsai,“Multiuser, Mobile, Multimedia Radio Network,”Wireless Networks, vol. 1, Oct. 1995, pp. 255–65.
[73].P. Basu, N. Khan, and T. D. C. Little,“A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks,”in Proc. IEEE ICDC-SW’01, Apr. 2001, pp. 413–18.
[74].A. B. McDonald and T. F. Znati,“Design and Performance of a Distributed Dynamic Clus-tering Algorithm for Ad-Hoc Networks,”in Proc. 34th Annual Simulation Symp., Apr. 2001, pp. 27–35.
[75].A. D. Amis and R. Prakash,“Load-Balancing Clusters in Wireless Ad Hoc Networks,”in Proc. 3rd IEEE ASSET’00, Mar. 2000, pp. 25–32.
[76].Wu, J., Li, H., On Calculating Connected Dominating Sets for Efficient Routing in Ad Hoc Wireless Networks, Proc. Third International Workshop on Discrete Algorithms and Meth-ods for Mobile Computing and Communications, (1999), pp. 7-14.
[77].J. Wu et al.,“On Calculating Power-Aware Connected Dominating Sets for Efficient Rout-ing in Ad Hoc Wireless Networks,”J. Commun. and Networks, vol. 4, no. 1, Mar. 2002, pp. 59–70.
[78].J.-H. Ryu, S. Song, and D.-H. Cho,“New Clustering Schemes for Energy Conservation in Two-Tiered Mobile Ad-Hoc Networks,”in Proc. IEEE ICC’01, vo1. 3, June 2001, pp. 862–66.
[79].T. Ohta, S. Inoue, and Y. Kakuda,“An Adaptive Multihop Clustering Scheme for Highly Mobile Ad Hoc Networks,”in Proc. 6th ISADS’03, Apr. 2003.
[80].M. Chatterjee, S. K. Das, and D. Turgut,“An On-Demand Weighted Clustering Algorithm (WCA) for Ad hoc Networks,”in Proc. IEEE Globecom’00, 2000, pp. 1697–701.
[81].Jian Ma, Quanbin Chen, Dian Zhang, Lionel M. Ni, "An empirical study of radio signal strength in sensor networks in using MICA2 nodes," HKUST, Technical Report, 2006.
[82].Crossbow Technologies, Inc., www.xbow.com;
[83].T. Camp, J. Boleng, and V. Davies,“Survey of mobility models for ad hoc network re-search”, WirelessCommunication and Mobile Computing (WCMC), vol. 2, 2002, pp. 483-502.
[84].S. Cho and J.P. Hayes, "Impact of mobility on connection stability in ad hoc networks”, in Proc. of Wireless Communication and Networking Conference (WCNC), New Orleans, LA, USA, March 2005.
[85].Akyildiz L.F., Su.W., Sankarasubramaniam Y. Wireless Sensor Networks: a Survey〔J〕.ComputerNetworks.2002, 38(4):393一422.
[86].N. Patwari and A. Hero. Using and Quantized RSS for Sensor Localization in Wireless Net-works. In Proc. 2nd ACM Intl. Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[87].V. Ramadurai and M. L. Sichitiu. Localization in Wireless Sensor Networks: A Probabilistic Approach. In Proc. 2003 Intl. Conf. on Wireless Networks (ICWN), pages 300–305, Las Vegas, NV, June 2003.
[88].S. Ray, R. Ungrangsi, F. De Pellegrini, A. Trachtenberg, and D. Starobinski. Robust Location Detection in Emergency Sensor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[89].J. Y. Yu and P. H. J. Chong,“3hBAC (3-hop between Adjacent Clusterheads): a Novel Non-overlapping Clustering Algorithm for Mobile Ad Hoc Networks,”in Proc. IEEE Pacrim’03, vol. 1, Aug. 2003, pp. 318–21.
[2].曾鹏,于海斌,梁英等. (J)信息与控制.2004,分布式无线传感器网络体系结构及应用支撑技术研究33(3):307一313.
[3].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(J).软件学报.2003,14(10):1717一1727.
[4].马祖长,孙怡宁,梅涛.无线传感器网络综述〔J〕.通信学报.2004,25(4): 114一124.
[5].A. Y. Wang, S. H. Cho, C. G. Sodini, and A. P. Chandrakasan. Energy Efficient Modulation and MAC for Asymmetric RF Microsensor ystems. In Intl. Symp. on Low Power Electronics and Design (ISLPED’01), pages 96–99, August 2001.
[6].C. Savarese, J. M. Rabaey, and J. Beutel. Locationing in Distributed Ad-Hoc Wireless Sensor Networks. In Proc. Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2001), Salt Lake City, Utah, May 2001.
[7].R.X. Gao and P. Hunerberg. CDMA-based wireless data transmitter for embedded sensors. In Proc. 18th IEEE Instrumentation and Measurement Technology Conf., volume 3, pages 1778–1783, 2001.
[8].E. Shih, S.-H. Cho, N. Ickes, R. Min, A. Sinha, A. Wang, and A. Chandrakasan. Physi-cal-Layer Driven Protocol and Algorithm Design for Energy-Efficient Wireless Sensor Net-works. In Proc 7th Ann. Intl. Conf. onMobile Computing and Networking, pages 272–286, Rome, Italy, July 2001. ACM.
[9].L. Charlie Zhong, R. C. Shah, C. Guo, and J. M. Rabaey. An Ultra-Low Power and Distrib-uted Access Protocol for Broadband Wireless Sensor Networks. In IEEE Broadband Wire-less Summit, Las Vegas, NV, May 2001.
[10].W. Ye, J. Heidemann, and D. Estrin. An energy-efficient MAC protocol for wireless sensor networks. In Proc. IEEE Infocom, 2002.
[11].K. Sohrabi, J. Gao, V. Ailawadhi, and G. J. Pottie. Protocols for self-organization of a wire-less sensor network. IEEE Personal Communications, 7(5):16–27, 2000.
[12].C. Schurgers, V. Tsiatsis, S. Ganeriwal, and M. B. Srivastava. Optimizing Sensor Networks in the Energy-Latency-Density Design Space. IEEE Transactions on Mobile Computing, 1(1), 2002.
[13].Y. Sankarasubramaniam, I.F. Akyildiz, and S.W.McLaughlin. Energy Efficiency Based Packet Size Optimization in Wireless Sensor Networks. In Proc. 1st IEEE Intl. Workshop onSensor Network Protocols and Applications (SNPA), Anchorage, AK, May 2003.
[14].M. Zorzi and R. R. Rao. Error Control and Energy Consumption in Communications for Nomadic Computing. IEEE Trans. on Computers, 46(3):279–289, 1997.
[15].E. Shih, B. Calhoun, S.-H. Cho, and A. Chandrakasan. Energy-Efficient Link Layer for Wireless Microsensor Networks. In Proc. Workshop on VLSI 2001 (WVLSI’01), April 2001.
[16].J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan. Build-ing Efficient Wireless Sensor Networks with Low-Level Naming. In Proc. Symp. on Operat-ing System Principles (SOSP 2001), pages 146–159, Lake Louise, Banff, Canada, October 2001.
[17].C. Schurgers, G. Kulkarni, and M. B. Srivastava. Distributed Assignment of Encoded MAC Addresses in Sensor Networks. In Proc. Symposium on Mobile Ad Hoc Networking & Computing (MobiHoc’01), Long Beach, CA, October 2001.
[18].W. Adjie-Winoto, E. Schwartz, H. Balakrishnan, and J. Lilley. The Design and Implementa-tion of an Intentional Naming System. In Proc. of the 7th ACM Symp. on Operating Systems Principles, pages 186–201. ACM Press, 1999.
[19].T. Berners-Lee, J. Hendler, and O. Lassila. The Semantic Web. Scientific American, May 2001. http://www.scientificamerican.com.
[20].A. Carzaniga and A. L. Wolf. Content-based Networking: A New Communication Infra-structure. In NSF Workshop on an Infrastructure for Mobile and Wireless Systems, Scotts-dale, Arizona, October 2001.
[21].W. R. Heinzelman, J. Kulik, and H. Balakrishnan. Adaptive Protocols for Information Dis-semination in Wireless Sensor Networks. In Proc. 5th Ann. Intl. Conf. on Mobile Computing and Networking, pages 174–185, Seattle, WA, August 2001. ACM. http://citeseer.nj.nec.
[22].J. Elson and K. Romer. Wireless sensor networks: a new regime for time synchronization. ACM SIGCOMM Computer Communication Review, 33(1):149–154, 2003.
[23].K. Romer. Time Synchronization in Ad Hoc Networks. In Proc. 2nd ACM Intl. Symp on Mobile Ad Hoc Networking and Computing, (MobiHoc), Long Beach, CA, 2001.
[24].J. van Greunen and J. Rabaey. Lightweight Time Synchronization for Sensor Networks. In Proc. 2nd ACM Intl. Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[25].W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. Energy-Efficient Communication Protocol for Wireless Microsensor Networks. In Proc. 33rd Hawaii Intl. Conf. on System Sciences, January 2000. http://www-mtl.mit.edu/?wendi/leach/hicss00.html
[26].S. Basagni, D. Turgut, and S. K. Das. Mobility-Adaptive Protocols for Managing Large Ad Hoc Networks. In Proc. of the IEEE Intl. Conf. on Communications (ICC), Helsinki, Finland, June 2001.
[27].T. J. Kwon andM. Gerla. Efficient flooding with Passive Clustering (PC) in ad hoc networks. ACM SIGCOMM Computer Communication Review, 32(1):44–56, 2002.
[28].P. Gupta and P. R. Kumar. Critical Power for Asymptotic Connectivity in Wireless Networks. In W.M. McEneany, G. Yin, and Q. Zhang, editors, Stochastic Analysis, Control, Optimiza-tion and Applications, pages 547–566. Birkhauser, Boston, 1998. http://black.csl.uiuc.edu/ prkumar/ps_files/connectivity.ps.
[29].M. Kubisch, H. Karl, A.Wolisz, L. C. Zhong, and J. Rabaey. Distributed Algorithms for Transmission Power Control in Wireless Sensor Networks. In Proc. IEEE Wireless Commu-nications and Networking Conference (WCNC), New Orleans, LA, March 2003.
[30].J. P. Monks, J.-P. Ebert, A. Wolisz, and W. W. Hwu. A Study of the Energy Saving and Ca-pacity Improvement Potential of Power Control in Multi-hop Wireless Networks. In Proc. of Workshop on Wireless Local Networks, Tampa, Florida, USA, November 2001. Held in conjunction with Conf. of Local Computer Networks (LCN).
[31].R. Ramanathan and R. Rosales-Hain. Topology Control of Multihop Wireless Networks us-ing Transmit Power Adjustement. In Proc. IEEE Infocom, Tel-Aviv, Israel, March 2000. http: //www.ieee-infocom.org/2000/papers/538.ps.
[32].P. Santi and D. M. Blough. The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks. IEEE Trans. on Mobile Computing, 2:25–39, March 2003.
[33].A. Safwat, H. Hassanein, and H. Mouftah. A MAC-based Performance Study of En-ergy-Aware Routing Schemes in Wireless Ad hoc Networks. In Proc. IEEE Globecom, 2002.
[34].R. Kannan, S. Sarangi, S. S. Iyengar, and L. Ray. Sensor-Centric Quality of Routing in Sen-sor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[35].J. Cartigny, D. Simplot, and I. Stojmenovic. Localized minimum-energy broadcasting in ad-hoc networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[36].A. K. Das, R. J. Marks, M. El-Sharkawi, P. Arabshabi, and A. Gray. Minimum Power Broadcast Trees for Wireless Networks: Integer Programming Formulations. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[37].C. Florens and R. McEliece. Packets Distribution Algorithms for Sensor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[38].W. Liang. Constructing Minimum -Energy Broadcast Trees in Wireless Ad Hoc Networks. In Proc. 3rd ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MobiHoc),Lausanne, Switzerland, 2002.
[39].J. Luo, P. Th. Eugster, and J.-P. Hubaux. Route Driven Gossip: Probabilistic Relibale Multi-cast in Ad Hoc Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[40].J. E. Wieselthier, G. D. Nguyen, and A. Ephremides. On the Construction of Energy-Efficient Broadcast and Multicast Trees in Wireless Networks. In Proc. IEEE Infocom, Tel-Aviv, Is-rael, March 2000.
[41].R. Cristescu and M. Vetterli. Power Efficient Gathering of Correlated Data: Optimization, NP-Completeness and Heuristics. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Net-working and Computing (MobiHoc), Annapolis, MD, 2003.
[42].S. Lindsey and K. M. Sivalingam. Data gathering algorithms in sensor networks using energy metrics. IEEE Trans. on Parallel and Distributed Systems, 13(9):924–934, 2002.
[43].F. Kuhn, R. Wattenhofer, and A. Zollinger. Worst-Case Optimal and Average-Case Efficient Geometric Ad-Hoc Routing. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MobiHoc), Annapolis, MD, 2003.
[44].M.Mauve, J.Widmer, and H. Hartenstein. A Survey on Position-Based Routing in Mobile Ad-Hoc Networks. IEEE Network, November 2001.
[45].Y. Xu, J. Heidemann, and D. Estrin. Geography-Informed Energy Conservation for Ad Hoc Routing. In Proc. 7th Ann. Intl. Conf. on Mobile Computing and Networking, pages 70–84, Rome, Italy, July 2001. ACM.
[46].P. Th. Eugster, P. A. Felber, R. Guerraoui, and A.-M. Kermarrec. The many faces of pub-lish/subscribe. ACM Computing Surveys (CSUR), 35(2):114–131, 2003.
[47].C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva. Directed Diffusion for Wireless Sensor Networking. IEEE Trans. on Networking, February 2003.
[48].J. Liu, F. Zhao, and D. Petrovic. Information-Directed Routing in Ad Hoc Sensor Networks. In Proc. 2nd ACM Intl.Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[49].S. Ratnasamy, P. Francis, M. Handley, R. Karp, and S. Shenker. A Scalable Con-tent-Addressable Network. In Proc. ACM SIGCOMM, 2001.
[50].Z. Fu, P. Zerfos, H. Luo, S. Lu, L. Zhang, andM. Gerla. The Impact of Multihop Wireless Channel on TCP Throughput and Loss. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[51].S.-J. Park and R. Sivakumar. Sink-to-Sensors Reliability in Sensor Networks. In Proc. 4th ACM Intl. Symp. on Mobile Ad Hoc Networking and Computing (MOBIHOC), Annapolis, MD, June 2003.
[52].Y. Sankarasubramaniam, O.B. Akan, and I.F. Akyildiz. ESRT: Event-to-Sink Reliable Transport in Wireless Sensor Networks. In Proc. ACM MOBIHOC 2003, Annapolis, Mary-land, USA, June 2003. ACM Press.
[53].F. Stann and J. Heideman. RMST: Reliable Data Transport in Sensor Networks. In Proc. 1st IEEE Intl.Workshop on Sensor Network Protocols and Applications (SNPA), Anchorage, AK,May 2003.
[54].C.-Y. Wan, A. T. Campbell, and L. Krishnamurthy. PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks. In Proc. 1st ACM Intl. Workshop on Sensor Networks and Ap-plications (WSNA), Atlanta, GA, September 2002.
[55].R. Want, A. Hopper, V. Falcao, and J. Gibbons,“The Active Badge Location System,”ACM Trans. Inf. Syst., vol. 10, no. 1, pp. 91–102, 1992;
[56].N. B. Priyantha, A. Chakraborty, and H. Balakri-shnan,“The Cricket location-support sys-tem,”in MobiCom’00: Proceedings of the 6th annual international conference on Mobile computing and networking. New York, NY, USA: ACM Press, 2000, pp. 32–43;
[57].P. Bahl and V. N. Padmanabhan,“RADAR: An In-Building RF-Based User Location and Tracking System.”in Proceedings of the IEEE INFOCOM 2000, 2000, pp. 775–784;
[58].Cisco System,“Data Sheet for Cisco Wireless Location Appliance,”Cisco Inc, Tech. Rep., 2005;
[59].Pete Steggles and Stephan Gschwind,“The Ubisense Smart Space Platform,”Ubisense Limited, Tech. Rep., May 2005;
[60].Yui-Wah Lee, Erich Stuntebeck, and Scott C. Miller,“MERIT: Mesh of RF Sensors for Indoor Tracking”, Secon’06, 2006;
[61].L.M. Ni, Y. Liu, Y.C. Lau, and A.P. Patil,“LANDMARC: Indoor Location Sensing Using Active RFID,”Wireless Networks, vol. 10, pp. 701–710, 2004;
[62].West, D., Introduction to Graph Theory, Second edition, Prentice Hall, Upper Saddle River, N.J., (2001)
[63].Chen, Y., P., Liestman, A. L., Approximating Minimum Size Weakly-Connected Dominating Sets for Clustering Mobile Ad Hoc Networks, 3rd ACM International Symposium on Mobile Ad Hoc Networks and Computing,(2002), pp. 165-72.
[64].Haynes, T., W., Hedetniemi, S., T., Slater, P., J., Domination in graphs, Advanced Topics, Marcel Dekker,Inc.,(1998).
[65].Baker, D., Ephremides, A., The Architectural Organization of a Mobile Radio Network via a Distributed Algorithm, Communications, IEEE Transactions, vol. 29-11, (1981), pp. 1694-1701.
[66].Gerla, M, Tsai, J. T., Multicluster, mobile, multimedia radio network, Wireless Networks, vol. 1(3), (1995),pp. 255-265.
[67].Chen, Y. P., Liestman, A.L., A Zonal Algorithm for Clustering Ad Hoc Networks, Interna-tional Journal of Foundations of Computer Science, vol. 14(2), (2003), pp. 305-322.
[68].Guha, S., Khuller, S., Approximation Algorithms for Connected Dominating Sets, Springer-Verlag New York,(1998), LLC, ISSN: 0178-4617.
[69].Stojmenovic, I., Seddigh, M., Zunic, J. Dominating sets and neighbor elimination-based broadcasting algorithms in wireless networks, IEEE Transactions on Parallel and Distributed Systems, (2002), pp. 14-25.
[70].C.-C. Chiang et al.,“Routing in Clustered Multihop, Mobile Wireless Networks with Fading Channel,”in Proc. IEEE SICON’97, 1997.
[71].A. Ephremides, J. E. Wieselthier, and D. J. Baker,“A Design Concept for Reliable Mobile Radio Networks with Frequency Hopping Signaling,”in Proc. IEEE, vol. 75, 1987, pp. 56–73.
[72].M. Gerla and J. T. Tsai,“Multiuser, Mobile, Multimedia Radio Network,”Wireless Networks, vol. 1, Oct. 1995, pp. 255–65.
[73].P. Basu, N. Khan, and T. D. C. Little,“A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks,”in Proc. IEEE ICDC-SW’01, Apr. 2001, pp. 413–18.
[74].A. B. McDonald and T. F. Znati,“Design and Performance of a Distributed Dynamic Clus-tering Algorithm for Ad-Hoc Networks,”in Proc. 34th Annual Simulation Symp., Apr. 2001, pp. 27–35.
[75].A. D. Amis and R. Prakash,“Load-Balancing Clusters in Wireless Ad Hoc Networks,”in Proc. 3rd IEEE ASSET’00, Mar. 2000, pp. 25–32.
[76].Wu, J., Li, H., On Calculating Connected Dominating Sets for Efficient Routing in Ad Hoc Wireless Networks, Proc. Third International Workshop on Discrete Algorithms and Meth-ods for Mobile Computing and Communications, (1999), pp. 7-14.
[77].J. Wu et al.,“On Calculating Power-Aware Connected Dominating Sets for Efficient Rout-ing in Ad Hoc Wireless Networks,”J. Commun. and Networks, vol. 4, no. 1, Mar. 2002, pp. 59–70.
[78].J.-H. Ryu, S. Song, and D.-H. Cho,“New Clustering Schemes for Energy Conservation in Two-Tiered Mobile Ad-Hoc Networks,”in Proc. IEEE ICC’01, vo1. 3, June 2001, pp. 862–66.
[79].T. Ohta, S. Inoue, and Y. Kakuda,“An Adaptive Multihop Clustering Scheme for Highly Mobile Ad Hoc Networks,”in Proc. 6th ISADS’03, Apr. 2003.
[80].M. Chatterjee, S. K. Das, and D. Turgut,“An On-Demand Weighted Clustering Algorithm (WCA) for Ad hoc Networks,”in Proc. IEEE Globecom’00, 2000, pp. 1697–701.
[81].Jian Ma, Quanbin Chen, Dian Zhang, Lionel M. Ni, "An empirical study of radio signal strength in sensor networks in using MICA2 nodes," HKUST, Technical Report, 2006.
[82].Crossbow Technologies, Inc., www.xbow.com;
[83].T. Camp, J. Boleng, and V. Davies,“Survey of mobility models for ad hoc network re-search”, WirelessCommunication and Mobile Computing (WCMC), vol. 2, 2002, pp. 483-502.
[84].S. Cho and J.P. Hayes, "Impact of mobility on connection stability in ad hoc networks”, in Proc. of Wireless Communication and Networking Conference (WCNC), New Orleans, LA, USA, March 2005.
[85].Akyildiz L.F., Su.W., Sankarasubramaniam Y. Wireless Sensor Networks: a Survey〔J〕.ComputerNetworks.2002, 38(4):393一422.
[86].N. Patwari and A. Hero. Using and Quantized RSS for Sensor Localization in Wireless Net-works. In Proc. 2nd ACM Intl. Workshop on Wireless Sensor Networks and Applications (WSNA), San Diego, CA, September 2003.
[87].V. Ramadurai and M. L. Sichitiu. Localization in Wireless Sensor Networks: A Probabilistic Approach. In Proc. 2003 Intl. Conf. on Wireless Networks (ICWN), pages 300–305, Las Vegas, NV, June 2003.
[88].S. Ray, R. Ungrangsi, F. De Pellegrini, A. Trachtenberg, and D. Starobinski. Robust Location Detection in Emergency Sensor Networks. In Proc. IEEE INFOCOM, San Francisco, CA, March 2003.
[89].J. Y. Yu and P. H. J. Chong,“3hBAC (3-hop between Adjacent Clusterheads): a Novel Non-overlapping Clustering Algorithm for Mobile Ad Hoc Networks,”in Proc. IEEE Pacrim’03, vol. 1, Aug. 2003, pp. 318–21.