The Community for Technology Leaders
Green Image
Issue No. 10 - Oct. (2011 vol. 22)
ISSN: 1045-9219
pp: 1757-1765
Hai Liu , Hong Kong Baptist University, Hong Kong
Xiaowen Chu , Hong Kong Baptist University, Hong Kong
Yiu-Wing Leung , Hong Kong Baptist University, Hong Kong
Xiaohua Jia , City University of Hong Kong, Hong Kong
Peng-Jun Wan , Illinois Institute of Technology, Chicago
We address a new and general maximal lifetime problem in sensor-target surveillance. We assume that each sensor can watch at most k targets (k \ge 1) and each target should be watched by h sensors (h \ge 1) at any time. The problem is to schedule sensors to watch targets and forward the sensed data to a base station such that the lifetime of the surveillance network is maximized. This general problem includes the existing ones as its special cases (k = 1 and h = 1 in [12] and k = 1 and h \ge 2 in [13]). It is also important in practice because some sensors can monitor multiple or all targets within their surveillance ranges and multisensor fusion (i.e., watching a target by multiple sensors) gives better surveillance results. The problem involves several subproblems and one of them is a new matching problem called (k, h)-matching. The (k, h)-matching problem is a generalized version of the classic bipartite matching problem (when k = h = 1, (k, h)-matching becomes bipartite matching). We design an efficient (k, h)-matching algorithm to solve the (k, h)-matching problem and then solve the general maximal lifetime problem. As a byproduct of this study, the (k, h)-matching problem and the proposed (k, h)-matching algorithm can potentially be applied to other problems in computer science and operations research.
Wireless sensor networks, maximal lifetime, scheduling, matching, routing.
Hai Liu, Xiaowen Chu, Yiu-Wing Leung, Xiaohua Jia, Peng-Jun Wan, "General Maximal Lifetime Sensor-Target Surveillance Problem and Its Solution", IEEE Transactions on Parallel & Distributed Systems, vol. 22, no. , pp. 1757-1765, Oct. 2011, doi:10.1109/TPDS.2011.42
94 ms
(Ver 3.3 (11022016))