Title
Algorithms for energy efficient mobile object tracking in wireless sensor networks
Abstract
Wireless sensor networks have found more and more applications in a variety of pervasive computing environments, in their functions as data acquisition in pervasive applications. However, how to get better performance to support data acquisition of pervasive applications over WSNs remains to be a nontrivial and challenging task. The network lifetime and application requirement are two fundamental, yet conflicting, design objectives in wireless sensor networks for tracking mobile objects. The application requirement is often correlated to the delay time within which the application can send its sensing data back to the users in tracking networks. In this paper we study the network lifetime maximization problem and the delay time minimization problem together. To make both problems tractable, we have the assumption that each sensor node keeps working since it turns on. And we formulate the network lifetime maximization problem as maximizing the number of sensor nodes who don't turn on, and the delay time minimization problem as minimizing the routing path length, after achieving the required tracking tasks. Since we prove the problems are NP-complete and APX-complete, we propose three heuristic algorithms to solve them. And we present several experiments to show the advantages and disadvantages referring to the network lifetime and the delay time among these three algorithms on three models, random graphs, grids and hypercubes. Furthermore, we implement the distributed version of these algorithms.
Year
DOI
Venue
2010
10.1007/s10586-009-0108-9
Cluster Computing
Keywords
Field
DocType
Wireless sensor network,Mobile object tracking,Algorithms,Network lifetime,Delay requirement
Sensor node,Key distribution in wireless sensor networks,Network delay,Heuristic,Computer science,Visual sensor network,Algorithm,Real-time computing,Mobile wireless sensor network,Ubiquitous computing,Wireless sensor network,Distributed computing
Journal
Volume
Issue
ISSN
13
2
1386-7857
Citations 
PageRank 
References 
10
0.52
26
Authors
3
Name
Order
Citations
PageRank
Li Liu163447.50
Bin Hu2778107.21
Lian Li318940.80