A gravitational search algorithm for solving the relay node placement problem in wireless sensor networks

Summary Nowadays, the use of wireless sensor networks (WSNs) is increasing in many fields of application, such as industrial monitoring, home automation, and intensive agriculture. However, this technology presents an important shortcoming, which has not been solved yet: the energy efficiency. This factor involves a critical economic disadvantage, affecting quality of service. This situation led us to tackle the relay node placement problem, that is, the addition of relay nodes to traditional WSNs as a way to optimize such networks, assuming two important factors: energy consumption and average coverage. To achieve this goal, three multi-objective (MO) evolutionary algorithms are considered (non-dominated sorting genetic algoritm II, strength Pareto evolutionary algorithm 2, and MO gravitational search algorithm), assuming a freely available data set and different stop criteria to analyze the behavior of the algorithms. All the results obtained are studied through a widely accepted statistical methodology and two MO metrics (hypervolume and set coverage), concluding that the novel swarm intelligence algorithm MO gravitational search algorithm provides the best performance on average. Moreover, we study the advantages provided by the addition of relay nodes to traditional WSNs. Finally, we compare our proposal with another author approach, assuming a heuristic. Copyright © 2015 John Wiley & Sons, Ltd.

[1]  Ding-Zhu Du,et al.  Improving Wireless Sensor Network Lifetime through Power Aware Organization , 2005, Wirel. Networks.

[2]  Guiran Chang,et al.  Energy efficient coverage control in wireless sensor networks based on multi-objective genetic algorithm , 2009, Comput. Math. Appl..

[3]  Yong-Hyuk Kim,et al.  An Efficient Genetic Algorithm for Maximum Coverage Deployment in Wireless Sensor Networks , 2013, IEEE Transactions on Cybernetics.

[4]  Siba K. Udgata,et al.  Sensor Deployment and Scheduling for Target Coverage Problem in Wireless Sensor Networks , 2014, IEEE Sensors Journal.

[5]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

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

[7]  Bang Wang,et al.  Coverage problems in sensor networks: A survey , 2011, CSUR.

[8]  L. Liu,et al.  Energy conservation algorithms for maintaining coverage and connectivity in wireless sensor networks , 2010, IET Commun..

[9]  Ali Peiravi,et al.  An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm , 2013, Int. J. Commun. Syst..

[10]  Xiuzhen Cheng,et al.  Strong Minimum Energy Topology in Wireless Sensor Networks: NP-Completeness and Heuristics , 2003, IEEE Trans. Mob. Comput..

[11]  Kun Yang,et al.  Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition , 2011, Comput. Commun..

[12]  Hichem Snoussi,et al.  Multi-objective optimization in wireless sensors networks , 2011, ICM 2011 Proceeding.

[13]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[14]  Miguel A. Labrador,et al.  A multiobjective approach to the relay placement problem in WSNs , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[15]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[16]  Miguel A. Vega-Rodríguez,et al.  A parallel evolutionary approach to solve the relay node placement problem in wireless sensor networks , 2013, GECCO '13.

[17]  H. Lilliefors.  On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[18]  Hossam S. Hassanein,et al.  Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks , 2010, IEEE Transactions on Mobile Computing.

[19]  Dina S. Deif,et al.  Classification of Wireless Sensor Networks Deployment Techniques , 2014, IEEE Communications Surveys & Tutorials.

[20]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[21]  Chunhua Zhao,et al.  Particle swarm optimization for optimal deployment of relay nodes in hybrid sensor networks , 2007, 2007 IEEE Congress on Evolutionary Computation.

[22]  Leandros Tassiulas,et al.  Maximum lifetime routing in wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

[23]  Lothar Thiele,et al.  A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizers , 2006 .

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

[25]  Satyajayant Misra,et al.  Constrained Relay Node Placement in Energy Harvesting Wireless Sensor Networks , 2011, 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems.

[26]  Jun Zhang,et al.  Hybrid Genetic Algorithm Using a Forward Encoding Scheme for Lifetime Maximization of Wireless Sensor Networks , 2010, IEEE Transactions on Evolutionary Computation.

[27]  Ashutosh Nigam,et al.  Optimal relay node placement in delay constrained wireless sensor network design , 2014, Eur. J. Oper. Res..

[28]  Hossam S. Hassanein,et al.  Transactions Papers - Device Placement for Heterogeneous Wireless Sensor Networks: Minimum Cost with Lifetime Constraints , 2007, IEEE Transactions on Wireless Communications.

[29]  Kamran Sayrafian-Pour,et al.  Distributed Deployment Algorithms for Improved Coverage in a Network of Wireless Mobile Sensors , 2014, IEEE Transactions on Industrial Informatics.

[30]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[31]  Jian Chen,et al.  Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius , 2009, Comput. Math. Appl..

[32]  W. Kruskal,et al.  Use of Ranks in One-Criterion Variance Analysis , 1952 .

[33]  Errol L. Lloyd,et al.  Relay Node Placement in Wireless Sensor Networks , 2011, IEEE Transactions on Computers.

[34]  Xiaofeng Han,et al.  Fault-Tolerant Relay Node Placement in Heterogeneous Wireless Sensor Networks , 2010, IEEE Trans. Mob. Comput..

[35]  Arunabha Sen,et al.  Relay node placement in large scale wireless sensor networks , 2006, Comput. Commun..

[36]  Y.T. Hou,et al.  On energy provisioning and relay node placement for wireless sensor networks , 2005, IEEE Transactions on Wireless Communications.

[37]  Andrea E. F. Clementi,et al.  Hardness Results for the Power Range Assignmet Problem in Packet Radio Networks , 1999, RANDOM-APPROX.

[38]  Eduardo G. Carrano,et al.  A Hybrid Multiobjective Evolutionary Approach for Improving the Performance of Wireless Sensor Networks , 2011, IEEE Sensors Journal.

[39]  S. Shapiro,et al.  An Analysis of Variance Test for Normality (Complete Samples) , 1965 .

[40]  Satyajayant Misra,et al.  Approximation Algorithms for Constrained Relay Node Placement in Energy Harvesting Wireless Sensor Networks , 2014, IEEE Transactions on Computers.

[41]  Qingfu Zhang,et al.  An Evolutionary Algorithm to a Multi-Objective Deployment and Power Assignment Problem in Wireless Sensor Networks , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.