Network lifetime maximization for time-sensitive data gathering in wireless sensor networks with a mobile sink

被引:18
作者
Liang, Weifa [1 ]
Luo, Jun [2 ]
Xu, Xu [1 ]
机构
[1] Australian Natl Univ, Res Sch Comp Sci, Canberra, ACT 0200, Australia
[2] Natl Univ Def Technol, Sch Comp Sci, Changsha, Hunan, Peoples R China
关键词
wireless sensor networks; sink mobility; data gathering; network lifetime maximization; distance-constrained shortest path; multiple-constrained joint optimization; load-balanced tree construction; network flow; sojourn time schedule;
D O I
10.1002/wcm.1179
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the advances of more and more mobile sink deployments (e.g., robots and unmanned aerial vehicles), mobile sinks have been demonstrated to play an important role in the prolongation of network lifetime. In this paper, we consider the network lifetime maximization problem for time-sensitive data gathering, which requires sensing data to be sent to the sink as soon as possible, subject to several constraints on the mobile sink. Because the mobile sink is powered by petrol or electricity, its maximum travel distance per tour is bounded. The mobile sink's maximum moving distance from its current location to the next must also be bounded to minimize data loss. As building a new routing tree rooted at each new location will incur an overhead on energy consumption, the mobile sink must sojourn at each chosen location at least for a certain amount of time. The problem, thus, is to find an optimal sojourn tour for the mobile sink such that the network lifetime is maximized, which is subject to a set of constraints on the mobile sink: its maximum travel distance, the maximum distance of each movement, and the minimum sojourn time at each sojourn location. In this paper, we first formulate this novel multiple-constrained optimization problem as the distance-constrained mobile sink problem for time-sensitive data gathering. We then devise a novel heuristic for it. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the performance of the proposed algorithm is very promising, and the solution obtained is fractional of the optimal one. Copyright (c) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:1263 / 1280
页数:18
相关论文
共 27 条
[21]   Optimizing Energy-Latency Trade-off in Sensor Networks with Controlled Mobility [J].
Sugihara, Ryo ;
Gupta, Rajesh K. .
IEEE INFOCOM 2009 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS, VOLS 1-5, 2009, :2566-2570
[22]  
Wang QS, 2009, FIFTEENTH ACM INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND NETWORKING (MOBICOM 2009), P121
[23]  
Wang Z.M., 2005, Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences, V9, P1, DOI DOI 10.1109/HICSS.2005.259
[24]  
Xing GL, 2008, MOBIHOC'08: PROCEEDINGS OF THE NINTH ACM INTERNATIONAL SYMPOSIUM ON MOBILE AD HOC NETWORKING AND COMPUTING, P231
[25]  
Xu X, 2010, IEEE INFOCOM SER
[26]   Strategies and techniques for node placement in wireless sensor networks: A survey [J].
Younis, Mohamed ;
Akkaya, Kemal .
AD HOC NETWORKS, 2008, 6 (04) :621-655
[27]   Maximizing the Lifetime of Wireless Sensor Networks with Mobile Sink in Delay-Tolerant Applications [J].
Yun, YoungSang ;
Xia, Ye .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2010, 9 (09) :1308-1318