An energy-efficient algorithm for object tracking in Wireless Sensor Networks

In recent years, due to the rapid growth of sensor technology and wireless communication, Wireless Sensor Networks (WSNs) have been applied to various applications. Nevertheless, sensor nodes are highly energy-constrained, because of the limitation of hardware and the infeasibility of recharging the battery under a harsh environment. Therefore, energy consumption of sensor nodes has become a popular issue. The purpose of this paper is to achieve energy-efficient object tracking for an arbitrary topology in WSNs. Object tracking typically contains two basic operations: update and query. Most research only considers the update cost during the design phase, or adjusts the structure by taking the query cost into consideration in the second round. We aim to construct an object tracking tree with minimum communication cost, including both update and query costs. This problem is formulated as an integer programming problem. The Lagrangean relaxation method is adopted to find an optimal solution and develop a heuristic algorithm for constructing an object tracking tree with minimum communication cost.

[1]  Yean-Fu Wen,et al.  A Tree-based Energy-Efficient Algorithm for Data-CentricWireless Sensor Networks , 2007, 21st International Conference on Advanced Information Networking and Applications (AINA '07).

[2]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[3]  Cheng-Ta Lee An Energy-Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks , 2009 .

[4]  Yean-Fu Wen,et al.  An Efficient Object Tracking Algorithm in Wireless Sensor Networks , 2006, JCIS.

[5]  H. T. Kung,et al.  Efficient location tracking using sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[6]  Cheng-Ta Lee,et al.  An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks , 2010, Sensors.

[7]  Li-Hsing Yen,et al.  Mobility Profiling Using Markov Chains for Tree-Based Object Tracking in Wireless Sensor Networks , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[8]  Yu-Chee Tseng,et al.  Message-efficient in-network location management in a multi-sink wireless sensor network , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[9]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[10]  Yu-Chee Tseng,et al.  Efficient in-network moving object tracking in wireless sensor networks , 2006, IEEE Transactions on Mobile Computing.

[11]  Marshall L. Fisher,et al.  The Lagrangian Relaxation Method for Solving Integer Programming Problems , 2004, Manag. Sci..

[12]  A. M. Geoffrion Lagrangean Relaxation and Its Uses in Integer Programming , 1972 .

[13]  Marshall L. Fisher,et al.  An Applications Oriented Guide to Lagrangian Relaxation , 1985 .

[14]  Bing-Hong Liu,et al.  Constructing a Message-Pruning Tree with Minimum Cost for Tracking Moving Objects in Wireless Sensor Networks Is NP-Complete and an Enhanced Data Aggregation Structure , 2008, IEEE Transactions on Computers.

[15]  Sania Bhatti,et al.  Survey of Target Tracking Protocols Using Wireless Sensor Network , 2009, 2009 Fifth International Conference on Wireless and Mobile Communications.

[16]  Yu-Chee Tseng,et al.  Message-efficient in-network location management in a multisink wireless sensor network , 2008, Int. J. Sens. Networks.