Previous [ 1] [ 2] [ 3] [ 4] [ 5] [ 6] [ 7] [ 8] [ 9] [ 10] [ 11] [ 12] [ 13] [ 14] [ 15] [ 16] [ 17] [ 18] [ 19] [ 20] [ 21] [ 22] [ 23] [ 24]


Journal of Information Science and Engineering, Vol. 27 No. 3, pp. 1091-1106 (May 2011)

Adaptive Path Planning for Randomly Deployed Wireless Sensor Networks*

Department of Computer Science and Engineering
+World Class University Future Network Optimization Technology Research Center
Korea University
Seoul, 136-701 Korea
+Department of Computer Science
University of Texas at Dallas
Richardson, TX 75083, U.S.A.

In this paper, we propose an adaptive path planning scheme considering the length of movement path and number of beacon messages of a mobile beacon for its energy efficiency, where the sensor nodes are randomly deployed. Contrary to the previous studies that utilize mobile beacons (nodes sending beacon messages) only on the basis of a random movement method or predefined static movement paths, the proposed scheme provides energy-efficient and adaptive movement path construction with low computational complexity. The movement path also includes beacon positions in which the mobile beacon broadcasts beacon messages containing the information of its current position. The random movement methods are not concerned about the energy of the mobile beacon. In randomly deployed environments, it is not easy to obtain precise field information for static movement path decisions. Thus, we propose the adaptive path planning scheme which can operate without this information in randomly deployed wireless sensor networks, and improve the energy efficiency of the mobile beacon. The candidate areas that limit the search space are devised so as to provide low complexity. The performance evaluation shows that the proposed scheme reduces the movement distance and number of beacon messages of the mobile beacon by comparison with other methods.

Keywords: mobile beacon, adaptive path planning, energy efficiency, randomly deployed WSNs, candidate areas

Full Text () Retrieve PDF document (201105_18.pdf)

Received August 13, 2009; revised March 8 & July 5 & August 18, 2010; accepted August 31, 2010.
Communicated by Wanjiun Liao.
* The preliminary version has been presented in the IEEE International Conference on Computer Communications and Networks, August 13-16, 2007, Turtle Bay Resort, Honolulu, Hawaii, USA, and it was supported by IEEE CommSoc (Technical Co-Sponsorship) and Nokia.