An evolutionary routing game for energy balance in Wireless Sensor Networks

Abstract In a Wireless Sensor Network (WSN), the sensor nodes rely on each other to forward packets from the origin to the base station via some routes. Computation of a desirable route is challenging. Some of the routes can be better than others, which might lead to an imbalance in contention for disparate routes as one route may be congested more frequently or exhausted quicker than the others. Since each node self-interest is to save its own energy due to the limited energy resource, it can lead to congestion resulting in higher delays and additional packet collisions– which may eventually result in quicker energy depletion along such routes and shorten the lifespan of the network. In this paper, we analyze this issue from a game theoretic perspective and model the route selection problem in a WSN as an evolutionary anti-coordination routing game. We derive the evolutionary stable strategy (ESS) of the game and prove that the derived incumbent strategy cannot be invaded by a greedy strategy i.e., mutant strategy. Furthermore, we derive the replicator dynamic of the proposed game in order to show the behavior of the sensors in selecting the paths. The mechanism of the replicator dynamics also shows how the nodes learn from their strategic interactions and modify their strategies at every stage of the game until reaching a stable strategy (ESS). Furthermore, the evolutionary game can be implemented in a distributed manner. Finally, in order to achieve increased lifetime, we analyze the fairness of the proposed equilibrium solution under the selfish node behavior by utilizing Jain’s fairness index. The results show that the proposed system is successful in converging the strategy choices to ESS even under dynamic conditions.

[1]  S. Sitharama Iyengar,et al.  Game-theoretic models for reliable path-length and energy-constrained routing with data aggregation in wireless sensor networks , 2004, IEEE Journal on Selected Areas in Communications.

[2]  Shengyong Chen,et al.  Game Theory for Wireless Sensor Networks: A Survey , 2012, Sensors.

[3]  Qiaoyan Wen,et al.  Energy Efficient Source Location Privacy Protecting Scheme in Wireless Sensor Networks Using Ant Colony Optimization , 2014, Int. J. Distributed Sens. Networks.

[4]  Chau Yuen,et al.  Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey , 2016, IEEE Communications Surveys & Tutorials.

[5]  Engin Zeydan,et al.  Energy-efficient routing for correlated data in wireless sensor networks , 2012, Ad Hoc Networks.

[6]  Yacine Challal,et al.  Energy efficiency in wireless sensor networks: A top-down survey , 2014, Comput. Networks.

[7]  P. Taylor,et al.  Evolutionarily Stable Strategies and Game Dynamics , 1978 .

[8]  Yong Deng,et al.  An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks , 2015, Int. J. Distributed Sens. Networks.

[9]  Mainak Chatterjee,et al.  Coexistence with malicious nodes: A game theoretic approach , 2009, 2009 International Conference on Game Theory for Networks.

[10]  K. Komathy,et al.  Trust-based evolutionary game model assisting AODV routing against selfishness , 2008, J. Netw. Comput. Appl..

[11]  Jean-Pierre Hubaux,et al.  Nuglets: a Virtual Currency to Stimulate Cooperation in Self-Organized Mobile Ad Hoc Networks , 2001 .

[12]  Karl Sigmund Evolutionary game dynamics : American Mathematical Society Short Course, January 4-5, 2011, New Orleans, Louisiana , 2011 .

[13]  Rachid Benlamri,et al.  Game theoretic energy balancing routing in three dimensional wireless sensor networks , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[14]  Zhide Chen,et al.  Incentive mechanism for selfish nodes in wireless sensor networks based on evolutionary game , 2011, Comput. Math. Appl..

[15]  Yezekael Hayel,et al.  An evolutionary game approach for the design of congestion control protocols in wireless networks , 2008, WiOpt 2008.

[16]  Eitan Altman,et al.  Evolutionary dynamics and potential games in non-cooperative routing , 2007, 2007 5th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks and Workshops.

[17]  Chau Yuen,et al.  Balancing Power Demand Through EV Mobility in Vehicle-to-Grid Mobile Energy Networks , 2016, IEEE Transactions on Industrial Informatics.

[18]  Zhu Han,et al.  Game Theory in Wireless and Communication Networks: Theory, Models, and Applications , 2011 .

[19]  Mohammad Reza Meybodi,et al.  A JOINT DUTY CYCLE SCHEDULING AND ENERGY AWARE ROUTING APPROACH BASED ON EVOLUTIONARY GAME FOR WIRELESS SENSOR NETWORKS , 2017 .

[20]  Vikram Krishnamurthy,et al.  Decentralized adaptation in sensor networks: Analysis and application of regret-based algorithms , 2007, 2007 46th IEEE Conference on Decision and Control.

[21]  Yinfeng Wu,et al.  Reliable routing in wireless sensor networks based on coalitional game theory , 2016, IET Commun..

[22]  Boleslaw K. Szymanski,et al.  Price based routing for event driven prioritized traffic in wireless sensor networks , 2013, 2013 IEEE 2nd Network Science Workshop (NSW).

[23]  Raj Jain,et al.  A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems , 1998, ArXiv.

[24]  Kourosh Eshghi,et al.  A Game Theory Approach for Optimal Routing: In Wireless Sensor Networks , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).