Fault Tolerance and Interference Aware Topology Control in Wireless Sensor Networks using NSGA-II
محورهای موضوعی : Majlesi Journal of Telecommunication DevicesNahid Sarbandi Farahani 1 , Asad Vakili 2
1 - Department of Computer, Saveh Branch,Islamic Azad University,Iran
2 - Iran Islamic Azad University/Department of Computer, Saveh, Iran
کلید واژه: Interference, Wireless Sensor Networks, Topology Control, throughput, NSGA-II algorithm, Fault tolerance,
چکیده مقاله :
Research on topology control protocols in wireless sensor networks has often been designed with the goal of creating a dynamic topology and extensibility. The present study focuses on finding high quality paths, instead of minimizing the number of hops that can cause reduction of the received signal strength and maximizing the rate of loss. The purpose of this research is to create a topology control that focuses on reducing the fault and minimizing interference simultaneously. For this purpose, the fault rate and the degree of interference minimizing functions are modeled by using a two-objective genetic algorithm. Since the genetic algorithm is a revelation algorithm, the proposed method is compared in terms of convergence with similar algorithms. The obtained graphs show that the proposed algorithm has a good degree of convergence compared to similar models. The "runtime", "memory consumption" and "energy required to transmit the statement" are the variables used to compare with similar algorithms. By observing the obtained graphs, the proposed algorithm compared to similar methods, reduces the time needed for topology control and also it lowers the energy consumption, but is not able to reduce memory consumption for more packages. The main reason for conducting the test is the comparison of the quality of the routes created, which were executed in 20 different requests with the number of routes 5, 10 and 20. The quality of the routes produced by the proposed method has a 1% improvement over the SMG method and a 3% compared to the PSO method according to the route quality criteria.
[1] E. Wilder, D. Castellanos, D. Juan, G. Pau, “A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks”, Computer Communications, vol. 77, pp 10-25, March. 2016.
[2] S. Palaniappan, P. Periasamy, “Quality of Service and Topology Control Protocol in Wireless Sensor Network: A Survey”, Journal of Signal Processing and Wireless Networks, vol. 2, No.1, pp. 1-12, 2016.
[3] K. Guleria., A. K. Verma, “Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks”, Wireless Netw 25, pp.1159-1183, April. 2019.
[4] M. Shyama, A. S. Pillai, “Fault-Tolerant Techniques for Wireless Sensor Network-A Comprehensive Survey”, Innovations in Electronics and Communication Engineering, vol. 65, pp. 261-269, February. 2019.
[5] M. Li, Z. Li and A. V. Vasilakos, “A Survey on Topology Control in Wireless Sensor Networks: Taxonomy, Comparative Study, and Open Issues”, in Proceedings of the IEEE, vol. 101, pp. 2538-2557, Dec. 2013
[6] J. Jia, X. Wang, J. Chen, J.yu, “Joint topology control and routing for multi-radio multi-channel WMNs under SINR model using bio-inspired techniques”, Applied Soft Computing, vol.32, pp. 49-58, July. 2015.
[7] Md. E. Haque, A. Rahman, “Fault Tolerant Interference-Aware Topology Control for Ad Wireless Networks”, international conference on Ad-hoc, mobile, and wireless networks, vol. 6811, pp. 100-116, 2011.
[8] M. Camelo, C. Omana, H. Castro, “QoS routing algorithms based on multi-objective optimization for mesh networks”, in IEEE Latin America Transactions, vol. 9, pp. 875-881, Sept. 2011.
[9] D. Chakraborti, P. Biswas, B. B. Pal, “FGP approach for solving fractional Multiobjective Decision making problems using GA with Tournament Selection and arithmetic crossover”, Procedia Technology, vol.10: pp. 505-514, Dec.2013.
[10] X. Bao, C. Deng, “FICTC: fault-tolerance-and-interference aware topology control for wireless multi-hop networks”, EURASIP Journal on Wireless Communications and Networking, pp.175-190, Aug.2016.
[11] J. Zhao, G. Cao, “Robust topology control in multi-hop cognitive radio networks”, IEEE Transactions on Mobile Computing, vol.13, pp. 2634-2647, Nov. 2014.
[12] I.C. Trelea, “The particle swarm optimization algorithm: convergence analysis and parameter selection”, Information Processing Letters, vol. 85, pp. 317-325, March.2003.
[13] M. Haidari, M. Asadpour, H. Faili, “SMG: Fast scalable greedy algorithm for influence maximization in social networks”, Physica A: Statistical Mechanics and its Applications, vol.420, pp. 124-133, Feb.2015.
[14] L. Cui, H. Hu, Sh. Yu, “DDSE: A novel evolutionary algorithm based on degree-descending search strategy for influence maximization in social networks”, Journal of Network and Computer Applications, vol.103, pp.119-130, Feb.2018.
[15] B. Zhang, Z. Jiao, C. Li, Z. Yao, and A. V. Vasilakos, “Efficient location-based topology control algorithms for wireless ad hoc and sensor networks”, Wireless Communications and Mobile Computing, vol. 16, pp. 1943–1955, Feb.2016.