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One of the most groundbreaking concepts in wireless networking is the mobile ad hoc network (MANET). It is an ever-shifting network of wireless nodes that may be adaptively and indiscriminately positioned, with the interconnections between nodes constantly changing. Defense networks, in particular, are becoming more prominent, and it is the goal and passion of technology to update and improve its components. There is a significant rise in transmission costs due to the high energy usage. Routing protocols have a critical role in reducing energy utilization. Weak routing protocol leads to exhaustive energy consumption, packet delay and packet loss. Ingenious Grey Wolf Optimization-based Routing Protocol (IGWORP) is proposed in this paper to discover the most efficient path to a destination and reduce the amount of delay and energy spent. IGWORP mirrors the natural tendencies of the grey wolf towards foraging for its prey. IGWORP looks for a global route rather than assembling many local routes. Encircling and hunting characteristics of wolves are used in IGWORP to discover and utilize the route for data transmission. Standard network metrics are used in NS3 to evaluate IGWORP's performance. The findings of IGWORP demonstrate that it reduces delays and energy consumption better than the current routing methods.

Keywords

Delay, Routing, Optimization, Wolf, Delay, Energy.

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References

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Ambient Intelligence-Based Fish Swarm Optimization Routing Protocol for Congestion Avoidance in Mobile Ad-Hoc Network

Abstract Views :196 | PDF Views:1

Authors

K. Sumathi ¹, D. Vimal Kumar ²

Affiliations
1 Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Computer Science, Nehru Arts and Science College, Coimbatore, IN

Source

International Journal of Computer Networks and Applications, Vol 9, No 3 (2022), Pagination: 340-349

Abstract

In mobile ad hoc networks, path stability estimation is a major difficulty because of connection failures that affect network nodes' mobility. In MANETs, path stability estimates must be based on a unified model that accounts for network node mobility and topology-triggered reactive path distribution statistics between surrounding nodes. It is possible to increase the collaboration between nodes in MANET by implementing an effective, trustworthy cum optimization-based routing protocol. This paper proposes the Ambient Intelligence-based Fish Swarm Optimization Routing Protocol (AIFSORP) to find the most efficient route to a destination and decrease the time and energy required. AIFSORP is designed to mimic the ant's innate instincts to forage its food. In AIFSORP, nodes quickly notify their neighbors when they discover a possible route to their target. Only when the route meets the threshold criterion is it picked for data transmission and shared with neighboring nodes. Optimization plays a significant part in AIFSORP towards determining the best route to the destination. AIFSORP's performance is evaluated using NS3s with standard network metrics. Compared to current routing systems, AIFSORP decreases delays and energy usage more effectively.

Keywords

Routing, Congestion, Delay, MANET, Optimization, Fish-Swarm.

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M. Zhang, M. Yang, Q. Wu, R. Zheng, and J. Zhu, “Smart perception and autonomic optimization: A novel bio-inspired hybrid routing protocol for MANETs,” Futur. Gener. Comput. Syst., vol. 81, pp. 505–

, 2018, doi: https://doi.org/10.1016/j.future.2017.07.030.

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K. Sumathi and D. Vimal Kumar, “Energy-Efficient Perspicacious Ant Colony Optimization Based Routing Protocol for Mobile Ad-Hoc Network,” Int. J. Comput. Networks Appl., doi: 10.22247/ijcna/2022/212339.

Invigorated Chameleon Swarm Optimization-Based Ad-Hoc On-Demand Distance Vector (ICSO-AODV) for Minimizing Energy Consumption in Healthcare Mobile Wireless Sensor Networks

Abstract Views :15 | PDF Views:0

Authors

S. Kawsalya ¹, D. Vimal Kumar ¹, D. Vimal Kumar ¹

Affiliations
1 Department of Computer Science, Nehru Arts and Science College, Coimbatore, Tamil Nadu, IN

Source

International Journal of Computer Networks and Applications, Vol 11, No 2 (2024), Pagination: 177-190

Abstract

This study explores the advancements in Wireless Sensor Networks (WSNs) and their application in Mobile Wireless Sensor Networks (MWSNs), particularly within Healthcare Mobile Wireless Sensor Networks (H-MWSNs). Routing in WSNs poses challenges, including adaptability to dynamic environments and efficient path computation. Addressing these challenges, this research propose the Floyd-Warshall-based Ad-hoc On-Demand Distance Vector (FW-AODV) approach. FW-AODV seamlessly integrates the Floyd-Warshall Algorithm with the AODV protocol, providing optimal path computation and dynamic routing capabilities. This integration is particularly promising for MWSNs, where adaptability and efficiency are crucial, especially in healthcare applications. We elucidate the working mechanism of FW-AODV, detailing its iterative rejuvenation process and dynamic color-based communication. Through simulations, this research evaluate FW-AODV's performance in dynamic and challenging WSN environments. Our results demonstrate FW-AODV's effectiveness in enhancing routing efficacy, resilience, and adaptability, offering a robust solution for modern healthcare-focused WSNs.

Keywords

FW-AODV, Optimal Path, Dynamic Routing, Chameleon Optimization, MWSN, Healthcare MWSN, Routing.

Full Text

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