International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

Energy Aware Geographic Routing Protocol using Evolutionary Algorithms for Improving QOS in MANET


Affiliations
1 Post-Doctoral Research Fellow, Institute of Computer Science and Information Science, Srinivas University, Mangalore, Karnataka, India
2 Professor, Institute of Computer Science and Information Science, Srinivas University, Karnataka, India
 

An energy-saving geographic routing is a crucial problem when trying to increase QoS and network life. In order for their adjacent neighbours to be able to reach effective routing performance, geographical routing nodes are necessary. However, the network's lifetime for efficient transmission has not been improved. In order to dynamically regulate the frequency of the position updates according to node movement dynamics, an updated position strategy for geographical routing is implemented. Various optimized geographical routing protocols have been designed to prevent interference between nodes, so that the data transmission did not improve easily. Nodes cannot easily save energy when transmitting data, which results in reduced network lifetime. On other hand, the reduction in the packet delivery ratio affects the overall throughput of the network. Anevolutionary technique based on geographical routing technology is introduced in this work to address the above limitations in current methods. To adopt evolutionary algorithms on Geographic Routing Protocol (GRP) to find optimal routing paths with reduced energy consumption and increased network lifetime. The work also carries out effective ways to avoid latency in delivering the packets from source to destination nodes.

Keywords

MANET, Geographic Routing Protocol, Evolutionary Technique, Optimization
User
Notifications
Font Size

  • Al-Mashaqbeh, G. A., Al-Karaki, J. N., AlRousan, M., Raza, A., Abbas, H., & Pasha, M. (2018). Joint Geographic and Energy-aware Routing Protocol for Static and Mobile Wireless Sensor Networks. Adhoc& Sensor Wireless Networks, 41.

  • Anand, N., Varma, S., Sharma, G., &Vidalis, S. (2018). Enhanced reliable reactive routing (ER3) protocol for multimedia applications in 3D wireless sensor networks. Multimedia Tools and Applications, 77(13), 16927-16946.

  • Benzerbadj, A., Kechar, B., Bounceur, A., & Pottier, B. (2018). Cross-Layer Greedy positionbased routing for multihop wireless sensor networks in a real environment. Ad Hoc Networks, 71, 135-146.

  • Chikh, A., &Lehsaini, M. (2018). Multipath routing protocols for wireless multimedia sensor networks: a survey. International Journal of Communication Networks and Distributed Systems, 20(1), 60-81.

  • Gao, Z. M., & Zhao, J. (2019). An Improved Grey Wolf Optimization Algorithm with Variable Weights. Computational Intelligence and Neuroscience, 2019.

  • Hadi, K. (2019). Analysis of Exploiting Geographic Routing for Data Aggregation in Wireless Sensor Networks. Procedia Computer Science, 151, 439-446.

  • Hao, K., Shen, H., Liu, Y., Wang, B., & Du, X. (2018). Integrating localization and energyawareness: A novel geographic routing protocol for underwater wireless sensor networks. Mobile Networks and Applications, 23(5), 1427-1435.

  • Hao, K., Shen, H., Liu, Y., Wang, B., & Du, X. (2018). Integrating localization and energyawareness: A novel geographic routing protocol for underwater wireless sensor networks. Mobile Networks and Applications, 23(5), 1427-1435.

  • Lu, T., Chang, S., & Li, W. (2018). Fog computing enabling geographic routing for urban area vehicular network. Peer-to-Peer Networking and Applications, 11(4), 749- 755.

  • Manjunath, D. R., &Thimmaraju, S. N. (2019). A Path Blind Approach to Secure Geographical Routing in Energy Aware Wireless Sensor Networks. Journal of Computational and Theoretical Nanoscience, 16(5-6), 2555-2566.

  • Qureshi, T. N., & Javaid, N. (2018, December). Enhanced adaptive geographic opportunistic routing with interference avoidance assisted with mobile sinks for underwater wireless sensor network. In 2018 International Conference on Frontiers of Information Technology (FIT) (pp. 367- 372). IEEE.

  • Majid Alotaibi. 2022. Geographic routing in mobile ad hoc networks (MANET) using hybrid optimization model: a multiobjective perspective. Applied Intelligence 53, 9 (May 2023), 11214–11228. https://doi.org/10.1007/s10489-022-03885- 7

  • Agrawal, Dr & Kapoor, Dr Monit. (2021). A comparative study on geographic‐based routing algorithms for flying ad‐hoc networks. Concurrency and Computation Practice and Experience. 33. 10.1002/cpe.6253.

  • Linqi Li, Xiaoyin Wang, Xinhua Ma, Design of a location-based opportunistic geographic routing protocol, Computer Communications, Volume 181, 2022, Pages 357- 364,https://doi.org/10.1016/j.comcom.2021 .10.030

  • Hamdy H. El-Sayed(2023). Minimizing Energy Hole Problem Comparisons in some Hierarchical WSN Routing Protocols, International Journal of Advanced Networking and Applications, Volume 15 Issue 5, Pages 5590-5595, https://doi.org/10.35444/IJANA.2023.1450 2


Abstract Views: 47

PDF Views: 1




  • Energy Aware Geographic Routing Protocol using Evolutionary Algorithms for Improving QOS in MANET

Abstract Views: 47  |  PDF Views: 1

Authors

J. VijiGripsy
Post-Doctoral Research Fellow, Institute of Computer Science and Information Science, Srinivas University, Mangalore, Karnataka, India
A. Jayanthiladevi
Professor, Institute of Computer Science and Information Science, Srinivas University, Karnataka, India

Abstract


An energy-saving geographic routing is a crucial problem when trying to increase QoS and network life. In order for their adjacent neighbours to be able to reach effective routing performance, geographical routing nodes are necessary. However, the network's lifetime for efficient transmission has not been improved. In order to dynamically regulate the frequency of the position updates according to node movement dynamics, an updated position strategy for geographical routing is implemented. Various optimized geographical routing protocols have been designed to prevent interference between nodes, so that the data transmission did not improve easily. Nodes cannot easily save energy when transmitting data, which results in reduced network lifetime. On other hand, the reduction in the packet delivery ratio affects the overall throughput of the network. Anevolutionary technique based on geographical routing technology is introduced in this work to address the above limitations in current methods. To adopt evolutionary algorithms on Geographic Routing Protocol (GRP) to find optimal routing paths with reduced energy consumption and increased network lifetime. The work also carries out effective ways to avoid latency in delivering the packets from source to destination nodes.

Keywords


MANET, Geographic Routing Protocol, Evolutionary Technique, Optimization

References