QoS Improvement using Enhanced Manhattan Mobility Model on Proposed Ant Colony Optimization Technique in MANETs

ACO OPTIMIZATION IN MOBILITY EFFICIENT MANETS

Authors

  • Satveer Kour Satveer Assistant Professor, Deptt. of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar 143 005, India
  • Jagpal Singh Ubhi Deptt. of ECE, Sant Longowal Institute of Engineering & Technology, Longowal 148 106, Sangrur, India
  • Manjit Singh Deptt. of Engineering and Technology, Guru Nanak Dev University Regional Campus, Jalandhar 144 009, India

DOI:

https://doi.org/10.56042/jsir.v82i06.1827

Keywords:

Bonnmotion-3.0.1, Mobility models, NS-2.35, Optimization, Routing protocols

Abstract

In the current Mobile Ad-hoc Network (MANET) route discovery procedure, traffic overflow and overhead may pose a major challenge for a path finding between communicating nodes. Swarm intelligence technique has been applied for various routing problems. We suggest an ant-based bottleneck routing method for MANET to identify weak links in the chosen route for routing overhead and delay issues. During data exchange, it selects the route using a swarm based technique called Ant Colony Optimization (ACO). Initially, we have created node  movements  by  Enhanced  Manhattan  Mobility  Model  (EMMM) and  then  a  bottleneck  value  based  ant colony optimization technique is applied. The simulation results show the improvement over existing ACO technique in terms of mobility and pause time. The Quality of Service (QoS) performance metrics showed improvement of 66% in drop rate, 141% in the packet delivery ratio, 42% in packet overhead, 171% in throughput, and 34% in the average end-to-end delay for mobility experiment. There is an improvement of 82% in drop rate, 108% in the packet delivery ratio, 45% in packet overhead, 171% in throughput, and 49% in the average end-to-end delay for a pause time experiment.

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Published

08-06-2023

Issue

Section

Computer Sciences, Communication and Information Technology

How to Cite

QoS Improvement using Enhanced Manhattan Mobility Model on Proposed Ant Colony Optimization Technique in MANETs: ACO OPTIMIZATION IN MOBILITY EFFICIENT MANETS. (2023). Journal of Scientific & Industrial Research (JSIR), 82(06), 616-628. https://doi.org/10.56042/jsir.v82i06.1827

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