Optimized Path Selection using GWO routing to enhance the lifetime of Sensor Node in WSN
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2021 by IJETT Journal|
|Year of Publication : 2021|
|Authors : M.Selvalakshmi, Dr.M.K.Jeyakumar
|DOI : 10.14445/22315381/IJETT-V69I4P226|
MLA Style: M.Selvalakshmi, Dr.M.K.Jeyakumar "Optimized Path Selection using GWO routing to enhance the lifetime of Sensor Node in WSN" International Journal of Engineering Trends and Technology 69.4(2021):183-187.
APA Style:M.Selvalakshmi, Dr.M.K.Jeyakumar. Optimized Path Selection using GWO routing to enhance the lifetime of Sensor Node in WSN International Journal of Engineering Trends and Technology, 69(4),183-187.
Wireless sensor networks are used in various fields to monitoring, sensing, and transmitting the information. Nowadays, it acts as a major role in the field of surveillance and health care medical applications. Even in this digital world, in risky places Replacing and recharging the batteries of sensor nodes are not possible. Many researchers focus on improving the lifetime of the sensor network. Various protocols are introduced for energy efficiency and consumption. Optimized path selection helps to transmit the data as soon as possible and avoid data congestion, and it consumes less energy. The proposed grid-based clustering FTM-GRP introduces GWO based routing algorithm to find the best-optimized path between the CH to sink and to the Base station for forwarding the data. MATLAB simulation results show the best performance in network stability and load balancing with less energy for the entire network.
 Ahmad, S. Jabbar, A. Paul, and S. Rho., Mobility aware energy-efficient congestion control in a mobile wireless sensor network., International Journal of Distributed Sensor Networks, Article ID530416, (2014) 13.
 A.W. Khan, A. H. Abdullah, M. A. Razzaque, and J. I. Bangash., VGDRA: a virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks, IEEE Sensors Journal, 15(1)(2015) 526–534.
 Amsalu, S. B., Zegeye, W. K., Hailemariam, D., Astatke, Y., & Moazzami, F., Energy-efficient Grid Clustering Hierarchy (GCH) routing protocol for wireless sensor networks. 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)., (2016).
 Bhatti R and Kaur G, "Virtual Grid-based energy-efficient mobile sink routing algorithm for WSN, 11th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, (2017) 30-33, doi: 10.1109/ISCO.2017.7856006.
 Bibin Christopher, V., & Jasper, J., DHGRP: Dynamic Hexagonal Grid Routing Protocol with Mobile Sink for Congestion Control in Wireless Sensor Networks. Wireless Personal Communications. doi:10.1007/s11277-020-07146-z ., (2020).
 D. C. Hoang, P. Yadav, R. Kumar, and S. K. Panda., Real-time implementation of a harmony search algorithm-based clustering protocol for energy-efficient wireless sensor networks, IEEE Transactions on Industrial Informatics, vol. 10(1)(2014) 774–783.
 Gou, P., Sun, M., Liu, X., Mao, G., & Li, F. (2019). Node Localization Algorithm Based on 3D Grid Partition and Meanshift Iteration for WSNs. 2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS), IEEE.,(2019).
 Huang, Q., Feng, Y., Li, X., & Huang, B., A Hexagonal Grid-Based Sink Relocation Method in Wireless Sensor Networks. 2015 Ninth International Conference on Frontier of Computer Science and Technology., (2015).
 Hui Zhang, A WSN Clustering Multi-Hop Routing Protocol Using Cellular Virtual Grid in IoT Environment, (2020), Mathematical Problems in Engineering
 H. Kareem and H. Jameel., Maintain Load Balancing in Wireless Sensor Networks Using Virtual Grid-Based Routing Protocol, 2018 International Conference on Advanced Science and Engineering (ICOASE), Duhok, (2018) 227-232, doi: 10.1109/ICOASE.2018.8548929.
 Khan, A. W., Bangash, J. I., Ahmed, A., & Abdullah, A. H., QDVGDD: Query-Driven Virtual Grid-based Data Dissemination for wireless sensor networks using the single mobile sink. Wireless Networks. doi:10.1007/s11276-017-1552-8 (2017).
 O. Dagdeviren, K. Erciyes, and S. Tse., Semi-asynchronous and distributed weighted connected dominating set algorithms for wireless sensor networks, Computer Standards and Interfaces, vol. 42(2015) 143–156.
 Selvalakshmi M, Jeyakumar M K., Enhanced Cluster Head Selection Approach for small scale and large scale network in WSN for improving energy efficiency. International Journal of Engineering Trends and Technology. 68(2020) 151-156. 10.14445/22315381/IJETT-V68I2P222S.
 Shih-Chang Huang., A Virtual-grid farmland data-gathering locations decision algorithm for the mobile sink in the wireless sensor network. 2015 Seventh International Conference on Ubiquitous and Future Networks..(2015).
 T. P. Sharma, R. C. Joshi, and M. Misra, GBDD: Grid-Based Data Dissemination in Wireless Sensor Networks, 2008 16th International Conference on Advanced Computing and Communications, Chennai, (2008) 234-240, doi: 10.1109/ADCOM.2008.4760454.
 V. Loscri, G. Morabito, and S. Marano, A two-level hierarchy for low-energy adaptive clustering hierarchy (TL-LEACH),” in Proceedings of the IEEE 62nd Vehicular Technology Conference (VTC ’05), 1809–1813, IEEE, (2005).
 Zhansheng Chen, Hong Shen, Beijing, A Grid-based Joint Routing and Energy Replenish Scheme for Rechargeable Wireless Sensor Networks, 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT).
 Sakthivel, B., & Padma, A., Area And Delay Efficient GDI Based Accuracy Configurable Adder Design. Microprocessors and Microsystems, 102958. doi:10.1016/j.micpro.2019.102958 .,(2019).
Virtual Grid, Meta Heuristics, Energy Consumption, Delay, Energy Efficiency