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Variants of ACO Comparisons for Network Routing Problem, An Analysis

Debabrata Singh, Chandan Kumar Panda, Sneha Patnaik

Abstract


Ant Colony Optimization (ACO) is a soft computing technique which enables to sketch out the shortest path. It is carried out by observing the ants. When ants find food at a particular place, they go in a single line following each other in order to reach the destination. If there is an obstruction in between then an ant changes its path. All the ants’ starts following the ant in order to reach the place fast considering the path as the shortest path. This basically happens due to the chemical secretion "Pheromones" by the ants. This is the whole mechanism of Ant Colony Optimization. There are many ant based algorithms. Previously these ant based algorithms were used to solve classical problems such as Travelling Salesman Problem (TSP), Classical Vehicle routing problems (VRP) etc. But algorithms have been gradually developed to solve Computer networking related problems including congestion problems too. It helps modifying continuously the routing table which in turn results in decreasing congestion problem. Congestion Problems includes Queuing delay, packet loss or blocking of new connections. These problems are the result of overloaded node. This leads to decrease in throughput of the system. The fundamental limitation leading to the above mentioned problem is limited resources including router processing time and link throughput. Using the limited resource and rescheduling the router repeatedly by using the Ant Colony Optimization technique will not only solve the problem but also will increase the system throughput.


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