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IJSTR >> Volume 9 - Issue 6, June 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



A Modified Power-Efficient Gathering in Sensor Information System (MOD-PEGASIS) for Routing in Wireless Sensor Network

[Full Text]

 

AUTHOR(S)

Navdeep Kumar Chopra, Rajesh Kumar Singh

 

KEYWORDS

Wireless Sensor Network, Power-efficient gathering in sensor information systems, Cuckoo search, Firefly, Artificial Neural Network.

 

ABSTRACT

Wireless Networking (WSN) uses numerous sensor nodes with multiple processing, sensing capabilities in order to monitor/ track a particular area which is far from a human approach. Because sensor nodes are mainly battery-powered and are extremely limited in terms of energy sources, it is necessary to explore energy optimization methods to extend the life of the WSN. In this research work, we mainly focused on to minimize the unnecessary wastage of energy and hence enhance the network performance. A Modified power-efficient gathering in sensor information systems (Mod-PEGASIS) algorithm is designed to select an appropriate Cluster Head (CH) by hybridizing the Cuckoo Search (CS) and Firefly algorithm. Initially, the sensor nodes are deployed in the defined network area on random basis. Then, the entire network is divided into different clusters each includes an individual CH. After the formation of optimal route, the selection of route is done using artificial neural network (ANN) approach. The simulation results illustrated that the designed approach can effectively improve the network performance in terms of end-to-end delay, packet drop ratio and energy consumption rate. The energy up to 4.52 % is obtained compared to the existing work.

 

REFERENCES

[1] Singh, Bipandeep, Er Simranjit Kaur, and Bipandeep Singh, “An Improved Energy-Efficient BBO-Based PEGASIS Protocol in Wireless Sensors Network,” Int. Journal of Engineering Research and Applications 4.3 (2014): 470-474.
[2] Weiwei Fang, Zhen Liu and Feng Liu, “A Cross-Layer Protocol For Reliable And Efficient Communication In Wireless Sensor Networks,” International Journal of Innovative Computing, 2012, Vol. 8, No. 18, October 2012.
[3] Cui, Z., Cao, Y., Cai, X., Cai, J., & Chen, J. “Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things”. Journal of Parallel and Distributed Computing, (2018)..
[4] Mareli, M., & Twala, B. “An adaptive Cuckoo search algorithm for optimization”. Applied Computing and informatics, 14(2), (2018), 107-115.
[5] Khabiri, M., & Ghaffari, A. “Energy-aware clustering-based routing in wireless sensor networks using cuckoo optimization algorithm”. Wireless Personal Communications, 98(3), (2018),.2473-2495.
[6] Gupta, V., & Doja, M. N. H-leach: “Modified and efficient leach protocol for hybrid clustering scenario in wireless sensor networks”. In Next-generation networks (pp. 399-408). (2018), Springer, Singapore.
[7] Somauroo, A., & Bassoo, V. “Energy-efficient genetic algorithm variants of PEGASIS for 3D Wireless Sensor Networks”. Applied Computing and Informatics, (2019).
[8] Biswas, S., Das, R., & Chatterjee, P. “Energy-efficient connected target coverage in multi-hop wireless sensor networks”. In Industry interactive innovations in science, engineering and technology (pp. 411-421), (2018), Springer, Singapore.
[9] Cheng, L., Niu, J., Luo, C., Shu, L., Kong, L., Zhao, Z., & Gu, Y. “Towards minimum-delay and energy-efficient flooding in low-duty-cycle wireless sensor networks”. Computer Networks, 134, (2018), 66-77.
[10] Wang, J., Ju, C., Gao, Y., Sangaiah, A. K., & Kim, G. J. “A PSO based energy efficient coverage control algorithm for wireless sensor networks”. Comput. Mater. Contin, 56, (2018), 433-446.
[11] Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. “A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network”. Wireless Networks, 24(6) (2018). 2061-2075.
[12] Sarkar, A., & Murugan, T. S. “Cluster head selection for energy efficient and delay-less routing in wireless sensor network”. Wireless Networks, 25(1), (2019). 303-320.
[13] Jia, J., Chen, J., Chang, G., Wen, Y., & Song, J. “Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius”. Computers & Mathematics with Applications, 57(11-12), (2009)., 1767-1775.
[14] Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. “Energy-efficient communication protocol for wireless microsensor networks”. In Proceedings of the 33rd annual Hawaii international conference on system sciences(pp. 10-pp). (2000, January). IEEE.
[15] Lindsey, S., & Raghavendra, C. S. PEGASIS: “Power-efficient gathering in sensor information systems”. In Proceedings, IEEE aerospace conference (Vol. 3, pp. 3-3). (2002, March). IEEE.
[16] Xie, G., & Pan, F. “Cluster-based routing for the mobile sink in wireless sensor networks with obstacles”. IEEE Access, 4, (2016), 2019-2028.
[17] Zhu, C., Wu, S., Han, G., Shu, L., & Wu, H. “A tree-cluster-based data-gathering algorithm for industrial WSNs with a mobile sink.” IEEE Access, 3, (2015).381-396.
[18] Ezhilarasi, M., & Krishnaveni, V. “An evolutionary multipath energy-efficient routing protocol (EMEER) for network lifetime enhancement in wireless sensor networks”. Soft Computing, (2019). 1-11.