About this Journal Submit a Manuscript Table of Contents
International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 794920, 10 pages
http://dx.doi.org/10.1155/2013/794920
Research Article

Dynamic Sensor Scheduling for Thermal Management in Biological Wireless Sensor Networks

1Department of Computer Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
2Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada K1S 5B6

Received 26 September 2012; Accepted 13 March 2013

Academic Editor: Nadjib Achir

Copyright © 2013 Yahya Osais et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Biological sensors are a very promising technology that will take healthcare to the next level. However, there are obstacles that must be overcome before the full potential of this technology can be realized. One such obstacle is that the heat generated by biological sensors implanted into a human body might damage the tissues around them. Dynamic sensor scheduling is one way to manage and evenly distribute the generated heat. In this paper, the dynamic sensor scheduling problem is formulated as a Markov decision process (MDP). Unlike previous works, the temperature increase in the tissues caused by the generated heat is incorporated into the model. The solution of the model gives an optimal policy that when executed will result in the maximum possible network lifetime under a constraint on the maximum temperature level tolerable by the patient’s body. In order to obtain the optimal policy in a lesser amount of time, two specific types of states are aggregated to produce a considerably smaller MDP model equivalent to the original one. Numerical and simulation results are presented to show the validity of the model and superiority of the optimal policy produced by it when compared with two policies one of which is specifically designed for biological wireless sensor networks.