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International Journal of Distributed Sensor Networks
Volume 2013 (2013), Article ID 794920, 10 pages
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.
- EGI Corporation, “Geodesic sensor networks,” http://www.egi.com/.
- “Pinnacle Technology,” http://www.pinnaclet.com/glucose.html.
- National Council on Radiation Protection and Measurements (NCRP), “A practical guide to the determination of human exposure to radiofrequency fields,” NCRP Report 119, 1993.
- International Electrotechnical Commission (IEC), Medical Electrical Equipment, Part 2-33: Particular Requirements for the Safety of Magnetic Resonance Equipment for Medical Diagnosis, IEC 60601-2-33, 2nd edition, 1995.
- H. H. Pennes, “Analysis of tissue and arterial blood temperatures in the resting human forearm,” Journal of Applied Physiology, vol. 1, no. 2, pp. 93–122, 1948.
- D. M. Sullivan, Electromagnetic Simulation Using the FDTD Method, IEEE Press, 2000.
- M. L. Puterman, Markov Decision Processes: Discrete Stochastic Dynamic Programming, Wiley, 2005.
- D. P. Bertsekas, Dynamic Programming and Optimal Control, vol. 1, Wiley, 1995.
- W. B. Powell, Approximate Dynamic Programming—Solving the Curse of Dimensionality, Wiley, 2007.
- H. S. Chang, M. C. Fu, J. Hu, and S. I. Marcus, Simulation-Based Algorithms for Markov Decision Processes, Springer, 2007.
- X.-R. Cao, Stochastic Learning and Optimization: A Sensitivity-Based Approach, Springer, 2007.
- J. Si, A. G. Barto, W. B. Powell, and D. Wunsch, Handbook of Learning and Approximate Dynamic Programming, Wiley-IEEE Press, 2004.
- Z. Ren and B. Krogh, “State aggregation in markov decision processes,” in Proceedings of the IEEE Conference on Decision and Control, pp. 3819–3824, December 2002.
- R. Givan, T. Dean, and M. Greig, “Equivalence notions and model minimization in Markov decision processes,” Artificial Intelligence, vol. 147, no. 1-2, pp. 163–223, 2003.
- P. Castro, P. Panangaden, and D. Precup, “Equivalence relations in fully and partially observable markov decision processes,” in Proceedings of the 21st International Joint Conference on Artificial Intelligence, pp. 1653–1658, Morgan Kaufmann, July 2009.
- N. Ferns, P. Panangaden, and D. Precup, “Metrics for finite markov decision processes,” in Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence, pp. 162–169, AUAI Press, July 2004.
- N. Ferns, P. Castro, D. Precup, and P. Panangaden, “Methods for computing state similarity in markov decision processes,” in Proceedings of the 22nd Conference in Uncertainty in Artificial Intelligence, pp. 174–181, AUAI Press, July 2006.
- Q. Tang, N. Tummala, S. K. S. Gupta, and L. Schwiebert, “Communication scheduling to minimize thermal effects of implanted biosensor networks in homogeneous tissue,” IEEE Transactions on Biomedical Engineering, vol. 52, no. 7, pp. 1285–1294, 2005.
- Q. Tang, N. Tummala, S. K. S. Gupta, and L. Schwiebert, “Tara: thermal-aware routing algorithm for implanted sensor networks,” in Distributed Computing in Sensor Systems, vol. 3560, pp. 206–217, Springer, 2005.
- Y. Chen, Q. Zhao, V. Krishnamurthy, and D. Djonin, “Transmission scheduling for optimizing sensor network lifetime: a stochastic shortest path approach,” IEEE Transactions on Signal Processing, vol. 55, no. 5, pp. 2294–2309, 2007.
- N. Jaggi, K. Kar, and A. Krishnamurthy, “Rechargeable sensor activation under temporally correlated events,” Wireless Networks, vol. 15, no. 5, pp. 619–635, 2009.
- G. Z. Yang, Body sensor networks [Ph.D. thesis], Cambridge University, Cambridge, UK, 2006.
- A. Seyedi and B. Sikdar, “Energy efficient transmission strategies for Body Sensor Networks with energy harvesting,” in Proceedings of the 42nd Annual Conference on Information Sciences and Systems (CISS '08), pp. 704–709, March 2008.
- J. G. Proakis, Digital Communications, McGraw-Hill, 2000.
- H. S. Wang and N. Moayeri, “Finite-state Markov channel—a useful model for radio communication channels,” IEEE Transactions on Vehicular Technology, vol. 44, no. 1, pp. 163–171, 1995.
- Q. Zhang and S. A. Kassam, “Finite-state markov model for rayleigh fading channels,” IEEE Transactions on Communications, vol. 47, no. 11, pp. 1688–1692, 1999.
- W. C. Jakes, Microwave Mobile Communications, Wiley, 1974.
- The MathWorks, http://www.mathworks.com/.