Energy efficiency in wireless sensor networks: A game-theoretic approach based on coalition formation

A coalitional game theoretic scheme is proposed that aims at maximizing wireless sensor network lifetime under specified QoS. Employing a small number of nodes of increased computing power and lifetime called representatives, an adaptive clustering scheme is proposed where neighboring nodes form coalitions in order to increase energy efficiency at the cost of controllable data-accuracy reduction. The coalition formation is globally optimized by the representatives. The spatial correlation of the sensed phenomenon measurements is exploited to formulate a cooperation scheme that reduces drastically the number of node transmissions. The specifications regarding the accuracy of the collected data determine the extent of coalition formation. The efficiency and stability of the proposed coalitional scheme are studied through simulations.

[1]  Debraj Ray A Game-Theoretic Perspective on Coalition Formation , 2007 .

[2]  Baltasar Beferull-Lozano,et al.  On network correlated data gathering , 2004, IEEE INFOCOM 2004.

[3]  Umesh Sehgal,et al.  AUTONOMIC WIRELESS SENSOR NETWORKS , 2012 .

[4]  Luigi Palopoli,et al.  Non-Transferable Utility Coalitional Games via Mixed-Integer Linear Constraints , 2010, J. Artif. Intell. Res..

[5]  R. J. Aumann,et al.  Cooperative games with coalition structures , 1974 .

[6]  Christian Schmidt,et al.  Game theory and economic analysis : a quiet revolution in economics , 2002 .

[7]  Stephen B. Wicker,et al.  Phase transition phenomena in wireless ad hoc networks , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[8]  I.F. Akyildiz,et al.  Spatial correlation-based collaborative medium access control in wireless sensor networks , 2006, IEEE/ACM Transactions on Networking.

[9]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[10]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[11]  Prateek Singh,et al.  Energy Efficiency in Wireless Sensor Network , 2015 .

[12]  Andreas Savvides,et al.  TASC: topology adaptive spatial clustering for sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[13]  Faramarz Fekri,et al.  Clustering-based correlation aware data aggregation for distributed sensor networks , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[14]  Tomasz Imielinski,et al.  Prediction-based monitoring in sensor networks: taking lessons from MPEG , 2001, CCRV.

[15]  Richard Tynan,et al.  Autonomic wireless sensor networks , 2004, Eng. Appl. Artif. Intell..

[16]  Sarvapali D. Ramchurn,et al.  Coalition formation with spatial and temporal constraints , 2010, AAMAS.

[17]  Johannes Gehrke,et al.  Query Processing in Sensor Networks , 2003, CIDR.

[18]  Xiaotie Deng,et al.  On the Complexity of Cooperative Solution Concepts , 1994, Math. Oper. Res..

[19]  Shiwei Tang,et al.  MCC: Model-Based Continuous Clustering in Wireless Sensor Networks , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[20]  Ambuj K. Singh,et al.  Distributed Spatial Clustering in Sensor Networks , 2006, EDBT.

[21]  Ramesh Govindan,et al.  The impact of spatial correlation on routing with compression in wireless sensor networks , 2008, TOSN.

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

[23]  Piotr Faliszewski,et al.  Constrained Coalition Formation , 2011, AAAI.

[24]  René van den Brink,et al.  Null or nullifying players: The difference between the Shapley value and equal division solutions , 2007, J. Econ. Theory.

[25]  Quanyan Zhu,et al.  A trade-off study between efficiency and fairness in communication networks , 2008, IEEE INFOCOM Workshops 2008.

[26]  Jie Wu,et al.  An unequal cluster-based routing protocol in wireless sensor networks , 2009, Wirel. Networks.

[27]  Konstantinos Psounis,et al.  Modeling spatially correlated data in sensor networks , 2006, TOSN.

[28]  Andreas Witzel,et al.  A Generic Approach to Coalition Formation , 2007, IGTR.

[29]  Onn Shehory,et al.  Coalition structure generation with worst case guarantees , 2022 .

[30]  Mohamed F. Younis,et al.  Overlapping Multihop Clustering for Wireless Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.

[31]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[32]  Zhu Han,et al.  Coalitional game theory for communication networks , 2009, IEEE Signal Processing Magazine.

[33]  Wendi B. Heinzelman,et al.  Prolonging the lifetime of wireless sensor networks via unequal clustering , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[34]  Mani B. Srivastava,et al.  Dynamic fine-grained localization in Ad-Hoc networks of sensors , 2001, MobiCom '01.

[35]  Cyrus Shahabi,et al.  The Clustered AGgregation (CAG) technique leveraging spatial and temporal correlations in wireless sensor networks , 2007, TOSN.