A Grey Wolf Optimization Approach for Improving the Performance of Wireless Sensor Networks

Optimizing the energy consumption of sensor nodes have been a big design issue in wireless sensor networks (WSNs). Energy efficient WSN usually compromise with network stability which is a crucial factor in ensuring full, lasting and reliable coverage of the network. Connected dominating set (CDS) based virtual backbone and traditional cluster based approach are two most commonly used data delivery protocols in a WSN. The paper proposes a distance based stable connected dominating set methodology using a meta-heuristic algorithm grey wolf optimization (DBSCDS-GWO) for achieving a stable, balanced and energy efficient CDS based WSN. We also propose a distance based stable clustering algorithm using GWO (DBSC-GWO) for improving the performance of cluster based WSN. DBSCDS-GWO performs better than RMCDS-GA and SAECDS-GA by 70.5% and 67.7% respectively and DBSC-GWO performs better than LEACH and DRESEP by 74.7% and 50.6% respectively in terms of both network stability and energy efficiency. Performance of the proposed algorithm is validated using Matlab simulation and Netsim Emulator.

[1]  Yi Pan,et al.  Greedy construction of load-balanced virtual backbones in wireless sensor networks , 2014, Wirel. Commun. Mob. Comput..

[2]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[3]  Yi Pan,et al.  Genetic-algorithm-based construction of Load-Balanced CDSs in Wireless Sensor Networks , 2011, 2011 - MILCOM 2011 Military Communications Conference.

[4]  Yi Pan,et al.  Load-balanced CDS construction in wireless sensor networks via genetic algorithm , 2012, Int. J. Sens. Networks.

[5]  Yi Pan,et al.  A Genetic Algorithm for Constructing a Reliable MCDS in Probabilistic Wireless Networks , 2011, WASA.

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

[7]  Suat Özdemir,et al.  Reliable and energy efficient topology control in probabilistic Wireless Sensor Networks via multi-objective optimization , 2016, The Journal of Supercomputing.

[8]  Aref Meddeb,et al.  Minimum energy multi-objective clustering model for Wireless Sensor Networks , 2016, 2016 International Wireless Communications and Mobile Computing Conference (IWCMC).

[9]  Eanoch Golden Julie,et al.  CDS-Fuzzy Opportunistic Routing Protocol for Wireless Sensor Networks , 2016, Wirel. Pers. Commun..

[10]  Shekhar Verma,et al.  A Power Aware Minimum Connected Dominating Set for Wireless Sensor Networks , 2009, J. Networks.

[11]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[12]  Deying Li,et al.  CDS-Based Virtual Backbone Construction with Guaranteed Routing Cost in Wireless Sensor Networks , 2013, IEEE Transactions on Parallel and Distributed Systems.

[13]  Peter J. Slater,et al.  Fundamentals of domination in graphs , 1998, Pure and applied mathematics.

[14]  Milan Tuba,et al.  Ant colony optimization algorithm with pheromone correction strategy for the minimum connected dominating set problem , 2013, Comput. Sci. Inf. Syst..

[15]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[16]  Urvinder Singh,et al.  Distance-Based Residual Energy-Efficient Stable Election Protocol for WSNs , 2015 .

[17]  Radhakrishnan Shanmugasundaram,et al.  Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks , 2015, Wirel. Pers. Commun..

[18]  Rachida Mekki,et al.  Routing Protocol Based on CDSE Virtual Topology in Ad Hoc Network , 2015, Wirel. Pers. Commun..

[19]  S. Guha,et al.  Approximation Algorithms for Connected Dominating Sets , 1998, Algorithmica.

[20]  Suat Özdemir,et al.  Prolonging stability period of CDS based WSNs , 2015, 2015 International Wireless Communications and Mobile Computing Conference (IWCMC).