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Adaptive Decentralized Clustering for Mobile Wireless Sensor Networks
|關鍵字:||mobile wireless sensor networks;移動式無線感測網路;clustering algorithm;random waiting timer;cluster maintenance;分群演算法;隨機等待計數器;群組維持||出版社:||通訊工程研究所||引用:|| C. Siva Ram Murthy and B.S. Manoj, “Ad Hoc Wireless Networks: Architectures and Protocols,” Prentice Hall, 2004.  E. M. Belding-Royer, “Hierarchical Routing in Ad Hoc Mobile Networks,” Wireless Commun. and Mobile Comp., vol. 2, no. 5, 2002, pp. 515-32.32  C. R. Lin and M. Gerla, “Adaptive Clustering for Mobile Wireless Networks,” IEEE JSAC, vol. 15, Sept. 1997, pp. 1265-75.  U. C. Kozat et al., “Virtual Dynamic Backbone for Mobile Ad Hoc Networks,” Proc. IEEE ICC'01, vol. 1, June 2001, pp. 250-55.  M. R. Pearlman and Z. J. Haas, “Determining the Optimal Configuration for the Zone Routing Protocol,” IEEE JSAC, vol. 17, Aug. 1999, pp. 1395-414.  A. Iwata et al., “Scalable Routing Strategies for Ad Hoc Wireless Networks,” IEEE JSAC, vol. 17, Aug. 1999, pp. 1369-79.  W. Chen, N. Jain, and S. Singh, “ANMP: Ad Hoc Network Management Protocol,” IEEE JSAC vol. 17, Aug. 1999, pp. 1506-31.  A.D. Amis, and R. Prakash, “Load-balancing clusters in wireless ad hoc networks,” in Proceedings of ASSET 2000 , Richardson, Texas, March 2000.  C.-Y. Wen and W. A. Sethares, “Automatic decentralized clustering for wireless sensor networks,” in EURASIP Journal on Wireless Communications and Networking, Volume 2005, Issue 5, pp. 686-697, December 2005.  H.C. Lin and Y.H. Chu, “A clustering technique for large multihop mobile wireless networks,” in Proceedings of the IEEE Vehicular Technology Conference, pp. 15-18, May 2000.  G. Venkataraman, et al., “Size-restricted cluster formation and cluster maintenance technique for mobile ad hoc networks,” in International Journal of Network Management, vol. 17, issue 2, pp. 171-194, March 2007.  D. J. Baker, A. Ephremides, and J. A. Flynn, “The design and simulation of a mobile radio network with distributed control,” in IEEE Journal on Selected Areas in Communications, SAC-2(1): pp. 226-237, 1984.  G. Venkataraman, et al., “A Novel Distributed Cluster Maintenance Technique for High Mobility Ad-hoc Networks,” Wireless Communication Systems, 2004. 1st International Symposium on Volume, Issue, 20-22, pages 225-229, Sept. 2004.  M. Cardei, J. Wu, and S.-H. Yang, “Topology control in ad hoc wireless networks using cooperative communication,” in IEEE Transactions on Mobile Computing, vol. 5, no. 6, pp. 711-724, June 2006.  Paolo Santi, Topology Control in Wireless Ad Hoc and Sensor Networks, John-Wiley & Sons, Inc 2005.  A. Ephremides, J. Wieselthier, and D. Baker, “A design concept for reliable mobile radio network with frequency hopping signaling,” in Proceedings of IEEE 75, pages 56-73, 1987.  A. K. Parekh, “Selecting routers in ad hoc wireless networks,” in ITS, 1994.  C.-C. Chiang, H.-K. Wu, W. Liu, and M. Gerla, “Routing in clustered multihop, mobile wireless networks with fading channel,” IEEE Singapore International Conference on Networks (SICON), pages 197- 211, Apr.1997.  P. Basu, N. Khan, and T. D. C. Little, “Mobility based metric for clustering in mobile ad hoc networks,” Workshop on Distributed Computing Systems, pages 413-418, 2001.  M. Chatterjee, S. K. Das, and D. Turgut, “WCA: A weighted clustering algorithm for mobile ad hoc networks,” Journal of Cluster Computing, Special issue on Mobile Ad hoc Networking, No. 5, pp. 193-204, 2002.  J. Lundelius and N. Lynch, “An upper and lower bound for clock synchronization.” Information and Control, Vol. 62 1984.  A. D. Amis, R. Prakash, T. H. P. Vuong and D. T. Huynh, “Max-Min D-Cluster Formation in Wireless Ad Hoc Networks,” in Proceedings of IEEE INFOCOM, March 2000.  A. B. McDonald, and T. Znati, “A mobility based framework for adaptive clustering in wireless ad-hoc networks,” in IEEE Journal on Selected Areas in Communications, Vol. 17, No. 8, pp. 1466-1487, Aug. 1999.  T. Ohta, S. Inoue, and Y. Kakuda, “An Adaptive Multihop Clustering Scheme for Highly Mobile Ad Hoc Networks,” in Proc. 6th ISADS'03, April 2003.  J.Y. Yu and P.H.J. Chong, “A survey of clustering schemes for mobile ad hoc networks,” in IEEE Communications Surveys & Tutorials, vol. 7, no. 1, pp. 32-48, First Quarter 2005.  F. Bai, N. Sadagopan, and A. Helmy, “IMPORTANT: a framework to systematically analyze the Impact of Mobility on Performance of Routing Protocols for Adhoc Networks,” in Proceedings of IEEE INFOCOM, March 2003.||摘要:||
近來年通訊技術、微型製造技術及嵌入式處理技術的提升，促使微小的感測器可以內嵌感測、計算及通訊等多樣化功能。此類感測器不但能偵測及感應環境的變化，更能分析所蒐集到的資訊，且透過無線通訊的功能將資料傳回至控制端。本篇論文針對行動式無線感測網路，提出適應性分散式群組化的演算法。在網路初始階段，每個感測器會利用各自的等待計數器(waiting timer)和區域性的資訊，決定是否加入現有的群組(cluster)或成立一個新的群組；而在等待計數器內，我們考量感測器周圍彼此的特性和移動速度，使得宣告自己為群組頭(clusterhead)的感測器在每個群組中具有較穩定的表現。除此之外，在群組成立期間，更加入了限制群組成員(clustermember)大小的參數，使得群組頭更能有效率地管理成員的個數。接著，再利用適當的準則，在群組中選擇出彼此間連結性較佳的閘道(gateway)來達到分散式拓樸的控制。由於網路拓樸隨著時間的變化，我們更進一步提出演算法來達成群組維持(cluster maintenance)的目的，即使感測器在網路中會不斷的任意移動，每個群組頭皆能平均地管理相同數量的群組成員，以避免某些群組頭有著太大的管理負擔。最後，透過模擬結果，我們觀察到系統整體的架構，發現感測器之間即使有著不相同的速度、數量密度或者是傳輸距離，都皆有穩定的表現。
Clustering for ad-hoc networks is an important issue since sensors in an infrastructure-less ad-hoc network may be required to self-organize. We propose a procedure to construct and maintain an effective hierarchical structure in mobile ad-hoc networks. This thesis proposes an adaptive decentralized clustering for mobile wireless sensor networks. At the beginning, based on a random waiting timer, each sensor either joins a nearby cluster, or else forms a new cluster with itself as clusterhead. Moreover, we take a number of metrics into account for cluster configuration, including neighboring node properties, and node mobility, which makes each clusterhead have a better performance. Furthermore, we restrict the cluster size to make clustermembers in each cluster more equivalent. Then, each cluster assigns gateways to connect with the neighboring clusters via local criterions. As we know that the entire sensor nodes in the network move arbitrarily as time proceeds, we further address some algorithms to maintain the linked cluster. Based on the proposed scheme, the loading for each clusterhead would be balanced. The simulation results show that the proposed algorithm provides stable performance regardless of varying node mobility, node density or transmission range.
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