International Journal of Advanced Networking and Applications

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Enhanced Particle Swarm Optimization based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing (EPSOGPSR) for Underwater Wireless Sensor Networks (UWSNs)


Affiliations
1 Assistant Professor (SG), Department of Computer Science, Nehru Arts and Science College, Coimbatore, India
2 Assistant Professor, Department of Information Technology, Nehru Arts and Science College, Coimbatore, India
 

EPSO-GPSR (Enhanced Particle Swarm Optimization-based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing), a unique strategy designed specifically for WSNs, is presented in this work. Using Enhanced Particle Swarm Optimization (EPSO) to provide load balancing across sensor nodes, the proposed EPSO-GPSR technique reduces energy disparities and increases the operational lifetime of the network. Additionally, it interfaces with the geographic routing protocol Greedy Perimeter Stateless Routing (GPSR) to enable effective data forwarding based on geographic locations, minimizing communication overhead and improving scalability. EPSO-GPSR's efficacy is shown against traditional load balancing and routing methods via comprehensive simulations and performance assessments. The network lifetime, energy efficiency, throughput, packet delivery ratio, and delay have all significantly showed better performance, according to the results. Additionally, the EPSO-GPSR algorithm demonstrates robustness against node failures and issues related to scalability, indicating a significant potential for real-world implementation in various WSN scenarios.

Keywords

Underwater Wireless Sensor Networks, load balancing, network lifetime, throughput, delay, packet delivery ratio, routing, greedy perimeter, stateless routing.
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  • Qian, L., Wu, Y., & Zhang, Y. (2008). Greedy perimeter stateless routing (GPSR) based on energy balance for Underwater Wireless Sensor Networks. In 2008 IEEE International Conference on Networking, SENSORS and Applications (ICNSA) (pp. 211-215). IEEE. doi: 10.1109/ICNSA.2008.4588605

  • Xu, Y., Zhang, D., & Hu, L. (2006). Energy-efficient greedy perimeter stateless routing for Underwater Wireless Sensor Networks. In 2006 International Conference on Wireless Communications, Networking and Mobile Computing (WICNM 2006) (pp. 89-92). IEEE. doi: 10.1109/WICNM.2006.4698389

  • Lin, C., & Sun, Y. (2009). An improved GPSR routing protocol for Underwater Wireless Sensor Networks based on energy balance. In 2009 Second International Conference on Networks and Communication (NeTCom '09) (pp. 174-178). IEEE. doi: 10.1109/NeTCOM.2009.4799641

  • Chen, C., & Yu, Z. (2010). A novel energy-efficient GPSR routing protocol for Underwater Wireless Sensor Networks based on adaptive multi-level clustering. In 2010 7th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM '10) (pp. 468-472). IEEE. doi: 10.1109/WiCOM.2010.5679330

  • Zong, K., Xu, X., Xu, W., & Zhang, H. (2011). An improved GPSR routing protocol based on energy balance and multi-hop for Underwater Wireless Sensor Networks. In 2011 International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM '11) (pp. 449-453). IEEE. doi: 10.1109/WiCOM.2011.6014133

  • Wang, J., & Li, J. (2012). An improved GPSR routing protocol based on energy balance and ant colony optimization for Underwater Wireless Sensor Networks. In 2012 International Conference on Computer Science and Information Engineering (CSIE 2012) (pp. 166-170). IEEE. doi: 10.1109/CSIE.2012.6896350

  • Kumar, D., & Lohan, A. (2013). An energy-efficient GPSR routing protocol for Underwater Wireless Sensor Networks based on fuzzy logic. In 2013 10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2013) (pp. 641-645). IEEE. doi: 10.1109/WiCOM.2013.6755724

  • Bera, S., & Sahu, P. K. (2014). An enhanced GPSR routing protocol based on hybrid clustering and multi-path routing for Underwater Wireless Sensor Networks. In 2014 International Conference on Advanced Computing and Communication Systems (ICACCS 2014) (pp. 227-232). IEEE. doi: 10.1109/ICACCS.2014.6810410

  • Al-Jarrah, A. A., & Mourad, H. (2016). A hybrid GPSR-AODV routing protocol for Underwater Wireless Sensor Networks. In 2016 International Conference on Networked Systems (NETSYS) (pp. 1-5). IEEE. doi: 10.1109/NETSYS.2016.7713382

  • Ali, M. Y. M., & Shehab, M. A. (2017). An improved GPSR routing protocol based on energy efficiency and load balancing for Underwater Wireless Sensor Networks. In 2017 IEEE 6th International Conference on Wireless & Mobile Computing, Networking & Communication (WiMob) (pp. 1-6). IEEE. doi: 10.1109/WiMob


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  • Enhanced Particle Swarm Optimization based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing (EPSOGPSR) for Underwater Wireless Sensor Networks (UWSNs)

Abstract Views: 122  |  PDF Views: 1

Authors

B. Narasimhan
Assistant Professor (SG), Department of Computer Science, Nehru Arts and Science College, Coimbatore, India
B. Karthikeyan
Assistant Professor, Department of Information Technology, Nehru Arts and Science College, Coimbatore, India

Abstract


EPSO-GPSR (Enhanced Particle Swarm Optimization-based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing), a unique strategy designed specifically for WSNs, is presented in this work. Using Enhanced Particle Swarm Optimization (EPSO) to provide load balancing across sensor nodes, the proposed EPSO-GPSR technique reduces energy disparities and increases the operational lifetime of the network. Additionally, it interfaces with the geographic routing protocol Greedy Perimeter Stateless Routing (GPSR) to enable effective data forwarding based on geographic locations, minimizing communication overhead and improving scalability. EPSO-GPSR's efficacy is shown against traditional load balancing and routing methods via comprehensive simulations and performance assessments. The network lifetime, energy efficiency, throughput, packet delivery ratio, and delay have all significantly showed better performance, according to the results. Additionally, the EPSO-GPSR algorithm demonstrates robustness against node failures and issues related to scalability, indicating a significant potential for real-world implementation in various WSN scenarios.

Keywords


Underwater Wireless Sensor Networks, load balancing, network lifetime, throughput, delay, packet delivery ratio, routing, greedy perimeter, stateless routing.

References