Cluster Optimization Based on Metaheuristic Algorithms in Wireless Sensor Networks

Partition of networks into optimal set of clusters is the prominent technique to prolong the network lifetime of energy constrained wireless sensor networks. Enumeration search method cannot find optimal clusters within polynomial bounded time for large scale networks since the computational complexity of problem grows exponentially with the dimension of networks. Optimal cluster configuration in sensor networks is known to be Non-deterministic Polynomial (NP)-hard optimization problem and for that reason we have applied polynomial time metaheuristic algorithms to find optimal or near-optimal solutions. In this paper, we present clustering algorithms based on Simulated Annealing (SA) and Particle Swarm Optimization (PSO) to find optimal set of cluster heads in the network. The optimization problem consists of finding optimal configuration of clusters such that the communication distance per cluster is not only minimized but the cluster balance and energy efficiency is also maintained in the network. The SA and PSO toolboxes are developed in C++ and integrated with OMNeT++ simulation environment to implement the proposed clustering algorithms. The performance of algorithms with respect to network lifetime, load balance and energy efficiency of network is examined in the simulation.

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

[2]  Ravi Sankar,et al.  A Survey of Intrusion Detection Systems in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[3]  Shashidhar Gandham,et al.  A Survey on Self-Organizing Wireless Sensor Networks , 2005, The Industrial Information Technology Handbook.

[4]  D. H. Smithgall,et al.  Toward the 60 gm wireless phone , 1998, Proceedings RAWCON 98. 1998 IEEE Radio and Wireless Conference (Cat. No.98EX194).

[5]  Pascal Chargé,et al.  A function approach for simple wireless sensor node energy consumption modeling , 2013, Proceedings of the 2013 Forum on specification and Design Languages (FDL).

[6]  Reza Monsefi,et al.  A multi-objective genetic algorithm based approach for energy efficient QoS-routing in two-tiered Wireless Sensor Networks , 2010, IEEE 5th International Symposium on Wireless Pervasive Computing 2010.

[7]  Peter Langendörfer,et al.  Application of wireless sensor networks in critical infrastructure protection: challenges and design options [Security and Privacy in Emerging Wireless Networks] , 2010, IEEE Wireless Communications.

[8]  Ramez Elmasri,et al.  Optimizing clustering algorithm in mobile ad hoc networks using simulated annealing , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[9]  Symeon Papavassiliou,et al.  On the energy-efficient organization and the lifetime of multi-hop sensor networks , 2003, IEEE Communications Letters.

[10]  Andre L. L. Aquino,et al.  Evolutionary design of wireless sensor networks based on complex networks , 2009, 2009 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

[11]  Yuhui Shi,et al.  Handbook of Swarm Intelligence: Concepts, Principles and Applications , 2011 .

[12]  D. Balmer.  Theoretical and Computational Aspects of Simulated Annealing , 1991 .

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

[14]  Ossama Younis,et al.  Node clustering in wireless sensor networks: recent developments and deployment challenges , 2006, IEEE Network.

[15]  Yu-Lin Tsou,et al.  Design, development and testing of a wireless sensor network for medical applications , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[16]  Chee-Yee Chong,et al.  Sensor networks: evolution, opportunities, and challenges , 2003, Proc. IEEE.

[17]  Yuhui Shi,et al.  Handbook of Swarm Intelligence , 2011 .

[18]  Hai Le Vu,et al.  An estimation of sensor energy consumption , 2009 .

[19]  A. Chandrakasan,et al.  Energy-efficient DSPs for wireless sensor networks , 2002, IEEE Signal Process. Mag..

[20]  Ameer Ahmed Abbasi,et al.  A survey on clustering algorithms for wireless sensor networks , 2007, Comput. Commun..

[21]  Charalampos Tsimenidis,et al.  Energy-Aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[22]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[23]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[24]  Nitin H. Vaidya,et al.  A MAC protocol to reduce sensor network energy consumption using a wakeup radio , 2005, IEEE Transactions on Mobile Computing.

[25]  Arunita Jaekel,et al.  Clustering strategies for improving the lifetime of two-tiered sensor networks , 2008, Comput. Commun..

[26]  George Papadopoulos.  Challenges in the design and implementation of Wireless Sensor Networks: A holistic approach-development and planning tools, middleware, power efficiency, interoperability , 2015, MECO.

[27]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[28]  Andrea J. Goldsmith,et al.  Design challenges for energy-constrained ad hoc wireless networks , 2002, IEEE Wirel. Commun..