Adaptation of the Ant Colony Algorithm to Avoid Congestion in Wireless Mesh Networks

Abstract: Wireless mesh networks have recently presented a promising environment for many researchers to develop large-scale wireless communication. Traffic in WMNs often suffers from congestion due to heavy traffic load’s saturation of certain routes. Therefore, this article proposes an efficient approach for congestion awareness and load balancing in WMNs, based on the Ant Colony Optimization (ACO) approach. The proposed approach aims to raise the performance of the WMN by distributing the traffic load between optimal routes and avoiding severe traffic congestion. The proposed approach relies on three basic mechanisms: detection of severe congestion within the ideal paths used for data transmission, creation of ideal secondary paths with updated pheromone values, and distribution of the traffic load (data packet flow) between the primary and secondary ideal paths. According to the results of the NS2 simulator, the suggested approach increased the WMN throughput by 14.8% when compared to the CACO approach and by 37% when employing the WCETT approach. The results also showed that the proposed approach achieved an average end-to-end delay closing of 0.0562, while WCETT and CACO approaches achieved an average end-to-end delay close to 0.1021 and 0.0976, respectively. The results indicated that the proposed approach achieved a lower percentage of dropped packets by 6.97% and 0.99% compared to the WCETT and CACO approaches. Thus, the proposed approach is effective in improving the performance of WMNs.

Adaptation of the Ant Colony Algorithm to Avoid Congestion in Wireless Mesh Networks| Journal of Cyber Security and Mobility (riverpublishers.com)

DOI: https://doi.org/10.13052/jcsm2245-1439.1258
Keywords: WMNs, ACO, congestion, traffic load, NS2

Fadhil Mohammed Salman, Ministry of Education, Babylon Education Directorate, Iraq, received his BS in computer science from the University of Anbar in Iraq in 2005. From 2010 to 2012, he completed his master’s in Computer Science from the Department of Computer Science University of Babylon, Iraq. He received his Ph.D. thesis in information technology from the Department of Software College of Information Technology University of Babylon, Iraq, in 2019. He has been a lecturer at the Babylon Education Directorate since 2007 till now. His research interests include computer networks, Network Security, Data compression, Image processing, and Data mining.

Ahssan Ahmed Mohammed Lehmoud, Ministry of Education, Babylon Education Directorate, Iraq, received his BS in computer science from the University of Babylon in Iraq in 2006. From 2009 to 2011, he completed his master’s in Computer Science from the Department of Computer Science and Information Technology at Dr. BabaSahib Ambedkar Marthwada University, India. He received his Ph.D. thesis in information technology from the Department of Software College of Information Technology University of Babylon, Iraq, in Abril 2018. He has been a lecturer at the Babylon Education Directorate since 2008 till now. His research interests include information security, Network security, Cryptography, Steganography, Image processing, and Data mining.

Fanar Ali Joda, Department of Air Conditioning & Refrigeration Engineering Techniques, Al-Mustaqbal University, Iraq. Ministry of Education, Babylon Education Directorate, Babylon, Iraq, on November 27, 1980. He received a BSc degree in computer science in 2002 from the University of Babylon/Computer Science Dept.-Iraq. He received the MSc in Data Compression 2015 from Babylon University – Iraq. He received his Ph.D. degree in Computer vision in 2019 from Babylon University-Iraq. Currently, Joda is Lecturer at Al-Mustaqbal University – Air Conditioning & Refrigeration Engineering Techniques Dept. His research interests include computer vision and information hiding.

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