Optimal distributed relay selection for duty-cycling Wireless Sensor Networks

Recent advances in localization technologies and algorithms for Wireless Sensor Networks (WSN) motivate the exploitation of location information in routing protocols. In this paper we consider the geographic forwarding of sporadically generated alarm messages. Our objective is to optimize sensor's energy consumption while respecting QoS constraints on transmission delay. For instance, we propose an optimal distributed relay selection policy for WSN with duty-cycling sensors based on a Markov Decision Process (MDP) with complete information. Also, we establish sufficient conditions for optimality of threshold policies. Then, end-to-end performances for a heuristic multi-hop relay selection strategy are established. Finally, we extend our model to account for queuing capabilities at sensor level.

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

[2]  Malcolm I. Heywood,et al.  Adding more intelligence to the network routing problem: AntNet and Ga-agents , 2006, Appl. Soft Comput..

[3]  Michael Gastpar,et al.  Cooperative strategies and capacity theorems for relay networks , 2005, IEEE Transactions on Information Theory.

[4]  Leonard Kleinrock,et al.  Optimal Transmission Ranges for Randomly Distributed Packet Radio Terminals , 1984, IEEE Trans. Commun..

[5]  B. Rozovskii,et al.  Optimal Stopping Rules , 1978 .

[6]  Guang Li,et al.  A Survey on Position-Based Routing Algorithms in Wireless Sensor Networks , 2009, Algorithms.

[7]  Gregory W. Wornell,et al.  Cooperative diversity in wireless networks: Efficient protocols and outage behavior , 2004, IEEE Transactions on Information Theory.

[8]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[9]  Jorge Urrutia,et al.  Compass routing on geometric networks , 1999, CCCG.

[10]  Kim R. Fowler The future of sensors and sensor networks survey results projecting the next 5 years , 2009, 2009 IEEE Sensors Applications Symposium.

[11]  Dharma P. Agrawal,et al.  QoS and energy aware routing for real-time traffic in wireless sensor networks , 2006, Comput. Commun..

[12]  Chenyang Lu,et al.  SPEED: a stateless protocol for real-time communication in sensor networks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[13]  Anurag Kumar,et al.  Relay Selection with Partial Information in Wireless Sensor Networks , 2011, ArXiv.

[14]  Anurag Kumar,et al.  Tunable Locally-Optimal Geographical Forwarding in Wireless Sensor Networks With Sleep-Wake Cycling Nodes , 2010, 2010 Proceedings IEEE INFOCOM.

[15]  Ian F. Akyildiz,et al.  A survey on wireless multimedia sensor networks , 2007, Comput. Networks.

[16]  Chang-Gun Lee,et al.  MMSPEED: multipath Multi-SPEED protocol for QoS guarantee of reliability and. Timeliness in wireless sensor networks , 2006, IEEE Transactions on Mobile Computing.

[17]  Vinod Sharma,et al.  Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node , 2009, 2009 IEEE International Conference on Communications.

[18]  Aggelos Bletsas,et al.  A simple Cooperative diversity method based on network path selection , 2005, IEEE Journal on Selected Areas in Communications.

[19]  Abdellatif Kobbane,et al.  QGRP: A Novel QoS-Geographic Routing Protocol for Multimedia Wireless Sensor Networks , 2012, ArXiv.

[20]  Brad Karp,et al.  GPSR: greedy perimeter stateless routing for wireless networks , 2000, MobiCom '00.

[21]  Mingyan Liu,et al.  Optimal Stochastic Routing in Low Duty-Cycled Wireless Sensor Networks , 2008, Internet Math..

[22]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

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

[24]  Albert N. Shiryaev,et al.  Optimal Stopping Rules , 1980, International Encyclopedia of Statistical Science.