Performance Analysis of Swarm Intelligence-Based Routing Protocol for Mobile Ad Hoc Network and Wireless Mesh Networks

• Main Author: Moghanjoughi, Ayyoub Akbari
• Format: Thesis
• Language: English; English
• Published: 2009
• Online Access: http://psasir.upm.edu.my/id/eprint/7834/1/abs_%3D%3D%3D_FK_2009_64.pdf; http://psasir.upm.edu.my/id/eprint/7834/
• Institution: Universiti Putra Malaysia

Ant colonies reside in social insect societies and maintain distributed systems that present a highly structured social organization despite of the simplicity of their individuals. Ants’ algorithm belongs to the Swarm Intelligence (SI), which is proposed to find the shortest path. Among various works inspired by ant colonies, the Ant Colony Optimization (ACO) metaheuristic algorithms are the most successful and popular, e.g., AntNet, Multiple Ant Colony Optimization (MACO) and AntHocNet. But there are several shortcomings including the freezing problem of the optimum path, traffic engineering, and to link failure due to nodes mobility in wireless mobile networks. The metaheuristic and distributed route discovery for data load management in Wireless Mesh Networks (WMNs) and Mobile Ad-hoc Network (MANET) are fundamental targets of this study. Also the main aim of this research is to solve the freezing problem during optimum as well as sub-optimum path discovery process. In this research, Intelligent AntNet based Routing Algorithm (IANRA) is presented for routing in WMNs and MANET to find optimum and near-optimum paths for data packet routing. In IANRA, a source node reactively sets up a path to a destination node at the beginning of each communication. This procedure uses ant-like agents to discover optimum and alternative paths. The fundamental point in IANRA is to find optimum and sub-optimum routes by the capability of breeding of ants. This ability is continuation of route that was produced by the parent ants. The new generations of ants inherit identifier of their family, the generation number, and the routing information that their parents get during their routing procedure. By this procedure, IANRA is able to prevent some of the existing difficulties in AntNet, MACO and Ad hoc On Demand Distance Vector (AODV) routing algorithms. OMNeT++ was used to simulate the IARNA algorithm for WMNs and MANET. The results show that the IANRA routing algorithm improved the data packet delivery ratio for both WMNs and MANET. Besides, it is able to decrease average end-to-end packet delay compared to other algorithms by showing its efficiency. IANRA has decreased average end-to-end packet delay by 31.16%, 58.20% and 48.40% in MANET scenario 52.86%, 64.52% and 62.86% by increasing packet generation rate in WMNs compared to AntHocNet, AODV and B-AntNet routing algorithms respectively with increased network load. On the other hand, IANRA shows the packet delivery ratio of 91.96% and 82.77% in MANET, 97.31% and 92.25% in WMNs for low (1 packet/s) and high (20 packet/s) data load respectively.