C19. Immune node deployment algorithm for mobile wireless sensor networks with limited mobility based on probabilistic sensing model

Coverage has direct effect on the network performance, thus it considered as the measure of quality of service in WSNs. The deployment strategy of sensor nodes in the sensor field is the most critical factor related to the network coverage. So, in this paper a centralized deployment algorithm based on immune optimization algorithm is proposed to improve the coverage of mobile sensor networks. The proposed algorithm redeploys the random deployed sensor nodes to maximize the coverage area based on a probabilistic sensing model. Moreover, the proposed algorithm limits the moving distance of mobile sensor nodes to reduce the dissipated energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the CSAPO algorithm using MATLAB simulation. Simulation results show that the proposed algorithm outperforms the CSAPO algorithm in terms of the network coverage, mobility cost and convergence speed.

[1]  T. Amudha,et al.  SOLVING JOB SHOP SCHEDULING PROBLEMS WITH CONSULTANT GUIDED SEARCH METAHEURISTICS , 2013 .

[2]  Mohammed Abo-Zahhad,et al.  Design of two-dimensional recursive digital filters with specified magnitude and group-delay characteristics using Taguchi-based Immune Algorithm , 2010 .

[3]  Wei Li,et al.  Improving wireless sensor network coverage using the VF-BBO algorithm , 2013, 2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM).

[4]  Po-Jen Chuang,et al.  Effective neural network-based node localisation scheme for wireless sensor networks , 2014, IET Wirel. Sens. Syst..

[5]  Li Hui,et al.  A Hybrid Deployment Algorithm Based on Clonal Selection and Artificial Physics Optimization for Wireless Sensor Network , 2013 .

[6]  Yipeng Qu,et al.  A centralized algorithm for prolonging the lifetime of wireless sensor networks using Particle Swarm Optimization , 2012, WAMICON 2012 IEEE Wireless & Microwave Technology Conference.

[7]  Yipeng Qu,et al.  Relocation of wireless sensor network nodes using a genetic algorithm , 2011, WAMICON 2011 Conference Proceedings.

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

[9]  Seong Yun Cho,et al.  Linear closed-form solution for wireless localisation with ultra-wideband/chirp spread spectrum signals based on difference of squared range measurements , 2013, IET Wirel. Sens. Syst..

[10]  Kamarulzaman Ab. Aziz,et al.  Coverage Maximization and Energy Conservation for Mobile Wireless Sensor Networks: A Two Phase Particle Swarm Optimization Algorithm , 2011, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications.

[11]  Miodrag Potkonjak,et al.  Sensor coverage in wireless sensor networks , 2005 .

[12]  Kamarulzaman Ab. Aziz,et al.  Coverage Maximization and Energy Conservation for Mobile Wireless Sensor Networks: A Two Phase Particle Swarm Optimization Algorithm , 2012, Int. J. Nat. Comput. Res..

[13]  Ahmad F. Al-Ajlouni,et al.  The Convergence Speed of Single- And Multi-Objective Immune Algorithm Based Optimization Problems , 2010 .

[14]  Dandan Liu,et al.  An Energy-Efficient Coverage Optimization Method for the Wireless Sensor Networks Based on Multi-objective Quantum-Inspired Cultural Algorithm , 2013, ISNN.