Lifetime Improvement Using Cluster Head Selection and Base Station Localization in Wireless Sensor Networks
محورهای موضوعی : Wireless Network
maryam najimi
1
(University of Science and Technology of Mazandaran)
Sajjad Nankhoshki
2
(University of Science and Technology of Mazandaran)
کلید واژه: Wireless Sensor Nodes , Network Lifetime , Particle Swarm Algorithm (PSO) , Base Station , Cluster Head,
چکیده مقاله :
The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most efficient techniques to save more energy in these networks. Therefore, the proper selection of the cluster heads plays important role to save the energy of sensor nodes for data transmission in the network. In this paper, we propose an energy efficient data transmission by determining the proper cluster heads in wireless sensor networks. We also obtain the optimal location of the base station according to the cluster heads to prolong the network lifetime. An efficient method is considered based on particle swarm algorithm (PSO) which is a nature inspired swarm intelligence based algorithm, modelled after observing the choreography of a flock of birds, to solve a sensor network optimization problem. In the proposed energy- efficient algorithm, cluster heads distance from the base station and their residual energy of the sensors nodes are important parameters for cluster head selection and base station localization. The simulation results show that our proposed algorithm improves the network lifetime and also more alive sensors are remained in the wireless network compared to the baseline algorithms in different situations.
The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most efficient techniques to save more energy in these networks. Therefore, the proper selection of the cluster heads plays important role to save the energy of sensor nodes for data transmission in the network. In this paper, we propose an energy efficient data transmission by determining the proper cluster heads in wireless sensor networks. We also obtain the optimal location of the base station according to the cluster heads to prolong the network lifetime. An efficient method is considered based on particle swarm algorithm (PSO) which is a nature inspired swarm intelligence based algorithm, modelled after observing the choreography of a flock of birds, to solve a sensor network optimization problem. In the proposed energy- efficient algorithm, cluster heads distance from the base station and their residual energy of the sensors nodes are important parameters for cluster head selection and base station localization. The simulation results show that our proposed algorithm improves the network lifetime and also more alive sensors are remained in the wireless network compared to the baseline algorithms in different situations.
[1] W. B. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy Efficient Communication Protocol for Wireless Microsensor Networks", in Proceedings Sciences, 2000, pp.1-10.
[2] L. Xiang, J. Luo, and A. Vasilakos, " Compressed Data Aggregation for Energy Efficient Wireless Sensor Networks", in 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Adhoc Communications and Networks (SECON), 2011, pp. 46–54.
[3] X. Y. Liu, Y. Zhu , L. Kong, C. Liu, Y. Gu, A. V. Vasilakos, and M.-Y. Wu, "CDC: Compressive Data Collection for Wireless Sensor Networks", IEEE Transactions on Parallel and Distributed Systems, Vol.26, No.8, 2015, pp. 2188–2197.
[4] X. Xu, R. Ansari, A. Khokhar, and A.V. Vasilakos, "Hierarchical Data Aggregation Using Compressive Sensing (HDACS) in WSNs", ACM Transactions on Sensor Networks (TOSN), Vol.11, No.3, 2015, pp.45-45.
[5] W. B. Heinzelman, A.P. Chandrakasan, and H. Balakrishnan, "An Application Specific Protocol Architecture for Wireless Microsensor Networks", IEEE Transactions on Wireless Communications, Vol.1, No.4,2002, pp.660–670.
[6] N. M. A. Latiff, C. C. Tsimenidis, and B. S. Sharif, "Energy-Aware Clustering for Wireless Sensor Networks Using Particle Swarm Optimization", in Proceedings of 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications,2007, pp. 1–5.
[7] B. Singh, and D.K. Lobiyal, "A Novel Energy-Aware Cluster Head Selection Based on Particle Swarm Optimization for Wireless Sensor Networks", Human-Centric Computing and Information Sciences Journal, Vo.l2, No.1, 2012 , pp.2–13.
[8] J. Roselin, P. Latha and S. Benitta, "Maximizing the Wireless Sensor Networks Lifetime through Energy Efficient Connected Coverage", Elsevier Adhoc Networks Journal, Vol.62, 2017, pp.1-10.
[9] S. Arjunan and P. Sujatha, "Lifetime maximization of wireless sensor network using fuzzy based unequal clustering and ACO based routing hybrid protocol", Applied Intelligence springer Journal, Vol.48, No.8, 2018, pp. 2229–2246.
[10] S. Jabbar, M. Ahmad, K.R. Malik, Sh. Khalid, J. Chaudhry and O. Aldabbas, "Designing an energy-aware mechanism for lifetime improvement of wireless sensor networks: a comprehensive study", Mobile Networks and Applications Springer Journal, Vol. 23, No.3, 2018, pp. 432–445.
[11] W. Y. Poe and J. B. Schmitt, "Minimizing the Maximum Delay in Wireless Sensor Networks by intelligent sink placement", Tech. Rep. 362/07, Distributed Computer Systems Lab, University of Kaiserslautern, Kaiserslautern, Germany, 2007.
[12] J. Pan, L. Cai, Y. T. Hou, Y. Shi and S. X. Shen, "Optimal Base Station Locations in Two-Tiered Wireless Sensor Networks", IEEE Transactions on Mobile Computing, Vol. 4, No. 5, 2005, pp. 458-473.
[13] M. 1. Showkat, B. Paul, M. A. Matin, and M. S Alam, "Optimal Sink Location in Wireless Sensor Networks Using Particle Swarm Optimization", in Proc. IEEE Interntional Conference on Antennas, Propagation and Systems (I A009), .Ihor Bahru, Malaysia, 2009, pp. 5445 – 5450.
[14] A. Ebrahimzadeh, M.Najimi, S. M. Hosseni Andargoli, and A. Fallahi, "Sensor Selection and Optimal Energy Detection Threshold for Efficient Cooperative Spectrum Sensing", IEEE Transaction on Vehicular Technology Journal, Vol.64, No.4, 2015, pp. 1565 – 1577.
[15] N. Aslam, and W. Phillips, W. Robertson and Sh. Sivakumar, "A Multi- Criterion Optimization Technique for Energy Efficient Cluster Formation in Wireless Sensor Networks", Information Fusion Journal in Press, Elsevier, Vol. 12. No.3, 2011, pp.202-212.
[16] M. Najimi, A. Ebrahimzadeh, S.M. Hosseni Andargoli, and A. Fallahi, "Lifetime Maximization in Cognitive Sensor Networks Based on the Node Selection", IEEE sensors Journal, Vol. 14, No. 7, 2014, pp.2376-2383.
[17] J. Kennedy, and R. Eberhart, "Particle Swarm Optimization", IEEE International Conference on Neural Networks, 1995, pp. 1942–1948.
[18] M. Azharuddin and P.K. Jana, "Particle Swarm Optimization for Maximizing Lifetime of Wireless Sensor Networks", Computers and Electrical Engineering Journal, Elsevier, Vol.51, 2016, pp.26-42.
[19] R.V. Kulkarni, and G.K. Venayagamoorthy, "Particle Swarm Optimization in Wireless Sensor Networks: A Brief Survey", IEEE Transactions on Systems, Vol.41, No.2, 2011, pp. 262-267.
[20] I.S. Akila, R. Venkatesan, and R. Abinaya, "A PSO Based Energy Efficient Clustering Approach for Wireless Sensor Networks", in IEEE International Conference on Computation of Power, Energy Information and Communication (ICCPEIC), 2016, pp.259-264.
[21] S. Maleki, A. Pandharipande, and G. Leus, "Energy-efficient distributed spectrum sensing for cognitive sensor networks", in Proceedings of 35th Annual Conference IEEE Industrial Electronics, 2009, pp. 2642–2646.
[22] S. Maleki, A. Pandharipande, and G. Leus, "Energy efficient distributed spectrum sensing with convex optimization", in Proceedings of 3rd International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2009, pp. 396–399.
[23] M. Najimi, A. Ebrahimzadeh, S.M. Hosseni Andargoli, and A. Fallahi, "A Novel Sensing Nodes and Decision Node Selection Method for Energy Efficiency of Cooperative Spectrum Sensing in Cognitive Sensor Networks", IEEE Sensors Journal, Vol.13, No.5, 2013, pp.1610-1621.
