Potential position node placement approach via oppositional gravitational search for fulfill coverage and connectivity in target based wireless sensor networks

Wireless Sensor Network (WSN) has appeared as a powerful technological platform with tremendous and novel applications. Now-a-days, monitoring and target tracking are the most major application in WSNs. In target based WSN, coverage and connectivity are the two most important issues for definite data forwarding from every target to a remote base station. An NP entire issue is to find least number of potential or possible locations to set sensor nodes gratifying both coverage and connectivity from a given a group of target points. In this article, we propose an Oppositional Gravitational Search algorithm (OGSA) based approach to solve this problem. This approach helps that the sensor nodes are prone to failure, the proposed system provides l-coverage to all targets and n-connectivity to each sensor node. This OGSA based system is presented with agent representation, derivation of efficient fitness function along with the usual Gravitational Search algorithm operators. The approach is simulated broadly with various scenarios of Wireless Sensor Network. The experimentation results are compared with some relevant existing algorithms to demonstrate the efficiency of the proposed approach.

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

[2]  Yi Liang,et al.  A Survey on Topology Control in Wireless Sensor Networks: Taxonomy, Comparative Study, and Open Issues , 2008, Proceedings of the IEEE.

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

[4]  Shusen Yang,et al.  A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities , 2013, IEEE Wireless Communications.

[5]  Mohamed F. Younis,et al.  Strategies and techniques for node placement in wireless sensor networks: A survey , 2008, Ad Hoc Networks.

[6]  David W. Coit,et al.  Multi-objective optimization using genetic algorithms: A tutorial , 2006, Reliab. Eng. Syst. Saf..

[7]  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..

[8]  Witold Pedrycz,et al.  An Evolutionary Multiobjective Sleep-Scheduling Scheme for Differentiated Coverage in Wireless Sensor Networks , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[9]  Athanasios V. Vasilakos,et al.  EDAL: An Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection Protocol for Wireless Sensor Networks , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[10]  Athanasios V. Vasilakos,et al.  Cross-Layer Support for Energy Efficient Routing in Wireless Sensor Networks , 2009, J. Sensors.

[11]  Athanasios V. Vasilakos,et al.  Directional routing and scheduling for green vehicular delay tolerant networks , 2012, Wireless Networks.

[12]  Athanasios V. Vasilakos,et al.  Approximating Congestion + Dilation in Networks via "Quality of Routing" Games , 2012, IEEE Trans. Computers.

[13]  Hamid R. Tizhoosh,et al.  Opposition-Based Learning: A New Scheme for Machine Intelligence , 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

[14]  Athanasios V. Vasilakos,et al.  Software-Defined and Virtualized Future Mobile and Wireless Networks: A Survey , 2014, Mobile Networks and Applications.

[15]  Prasanta K. Jana,et al.  Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach , 2014, Eng. Appl. Artif. Intell..

[16]  Prasanta K. Jana,et al.  Genetic Algorithm for k-Connected Relay Node Placement in Wireless Sensor Networks , 2016 .

[17]  Juan Antonio Gómez Pulido,et al.  Assuming multiobjective metaheuristics to solve a three-objective optimisation problem for Relay Node deployment in Wireless Sensor Networks , 2015, Appl. Soft Comput..

[18]  Bijaya K. Panigrahi,et al.  Multi-objective node deployment in WSNs: In search of an optimal trade-off among coverage, lifetime, energy consumption, and connectivity , 2013, Eng. Appl. Artif. Intell..

[19]  Athanasios V. Vasilakos,et al.  Local Area Prediction-Based Mobile Target Tracking in Wireless Sensor Networks , 2015, IEEE Transactions on Computers.

[20]  Athanasios V. Vasilakos,et al.  A Biology-Based Algorithm to Minimal Exposure Problem of Wireless Sensor Networks , 2014, IEEE Transactions on Network and Service Management.

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

[22]  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.

[23]  Athanasios V. Vasilakos,et al.  Physarum Optimization: A Biology-Inspired Algorithm for the Steiner Tree Problem in Networks , 2015, IEEE Transactions on Computers.

[24]  Athanasios V. Vasilakos,et al.  Spatial Reusability-Aware Routing in Multi-Hop Wireless Networks , 2016, IEEE Transactions on Computers.

[25]  Prasanta K. Jana,et al.  Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks , 2015, Comput. Electr. Eng..

[26]  Athanasios V. Vasilakos,et al.  A generic framework for energy evaluation on wireless sensor networks , 2015, Wireless Networks.

[27]  Özlem Durmaz Incel,et al.  QoS-aware MAC protocols for wireless sensor networks: A survey , 2011, Comput. Networks.

[28]  A. Ebenezer Jeyakumar,et al.  Hybrid PSO–SQP for economic dispatch with valve-point effect , 2004 .

[29]  Hongsheng Chen,et al.  Probabilistic coverage based sensor scheduling for target tracking sensor networks , 2015, Inf. Sci..

[30]  Athanasios V. Vasilakos,et al.  Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter , 2011, Comput. Commun..

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

[32]  Prasanta K. Jana,et al.  A novel evolutionary approach for load balanced clustering problem for wireless sensor networks , 2013, Swarm Evol. Comput..

[33]  Bing-Hong Liu,et al.  Constructing a Wireless Sensor Network to Fully Cover Critical Grids by Deploying Minimum Sensors on Grid Points Is NP-Complete , 2007, IEEE Transactions on Computers.

[34]  Athanasios V. Vasilakos,et al.  Compressed data aggregation for energy efficient wireless sensor networks , 2011, 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[35]  Arunita Jaekel,et al.  Design of fault tolerant wireless sensor networks satisfying survivability and lifetime requirements , 2012, Comput. Commun..

[36]  Aybars Uğur,et al.  Maximizing Coverage in a Connected and K-Covered Wireless Sensor Network Using Genetic Algorithms , 2008 .

[37]  Siba K. Udgata,et al.  Connected Coverage Problem in Wireless Sensor Networks , 2012 .

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

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

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

[41]  Prasanta K. Jana,et al.  GAR: An Energy Efficient GA-Based Routing for Wireless Sensor Networks , 2013, ICDCIT.

[42]  Hichem Snoussi,et al.  Sensor deployment optimization methods to achieve both coverage and connectivity in wireless sensor networks , 2015, Comput. Oper. Res..

[43]  Athanasios V. Vasilakos,et al.  Tight Performance Bounds of Multihop Fair Access for MAC Protocols in Wireless Sensor Networks and Underwater Sensor Networks , 2012, IEEE Transactions on Mobile Computing.

[44]  Naixue Xiong,et al.  Multi-layer clustering routing algorithm for wireless vehicular sensor networks , 2010, IET Commun..

[45]  Prasanta K. Jana,et al.  A novel differential evolution based clustering algorithm for wireless sensor networks , 2014, Appl. Soft Comput..

[46]  Athanasios V. Vasilakos,et al.  Algorithm design for data communications in duty-cycled wireless sensor networks: A survey , 2013, IEEE Communications Magazine.

[47]  Prasanta K. Jana,et al.  Genetic algorithm approach for k-coverage and m-connected node placement in target based wireless sensor networks , 2016, Comput. Electr. Eng..