An MDP-based application oriented optimal policy for wireless sensor networks

Technological advancements due to Moore's law have led to the proliferation of complex wireless sensor network (WSN) domains. One commonality across all WSN domains is the need to meet application requirements (i.e. lifetime, responsiveness, etc.) through domain specific sensor node design. Techniques such as sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e. processor voltage and frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN domain diversity, varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very challenging task. In this paper, we propose an automated Markov Decision Process (MDP)-based methodology to prescribe optimal sensor node operation (selection of values for tunable parameters such as processor voltage, processor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more closely meets application requirements compared to other feasible policies.

[1]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[2]  Anantha P. Chandrakasan,et al.  Dynamic voltage scaling techniques for distributed microsensor networks , 2000, Proceedings IEEE Computer Society Workshop on VLSI 2000. System Design for a System-on-Chip Era.

[3]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.

[4]  Gang Qu,et al.  Design space exploration for energy-efficient secure sensor network , 2002, Proceedings IEEE International Conference on Application- Specific Systems, Architectures, and Processors.

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

[6]  Nael B. Abu-Ghazaleh,et al.  Infrastructure tradeoffs for sensor networks , 2002, WSNA '02.

[7]  Sandeep Neema,et al.  Constraint-guided dynamic reconfiguration in sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[8]  Mahmut T. Kandemir,et al.  Tuning in-sensor data filtering to reduce energy consumption in wireless sensor networks , 2004, Proceedings Design, Automation and Test in Europe Conference and Exhibition.

[9]  David E. Culler,et al.  System software techniques for low-power operation in wireless sensor networks , 2005, ICCAD-2005. IEEE/ACM International Conference on Computer-Aided Design, 2005..

[10]  David E. Culler,et al.  Design of a wireless sensor network platform for detecting rare, random, and ephemeral events , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[11]  Susan Lysecky,et al.  A First Step Towards Dynamic Profiling of Sensor-Based Systems , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[12]  Vincent W. S. Wong,et al.  An MDP-Based Vertical Handoff Decision Algorithm for Heterogeneous Wireless Networks , 2008, IEEE Transactions on Vehicular Technology.