An Evaluation Of Ant Colony Optimization Based Techniques for Network Load Balancing

This study uses the Ant Colony Optimization (ACO) algorithm to evaluate the network load balance. The main objectives of the ACO are to decrease execution time and achieve a balanced overall distribution of workloads among the network‘s nodes. There are two priorities of the ACO load balancing algorithm which is first is to ensure the number of tasks assigned to each node with the networking environment are as uniform. Next priority is to select a node with the best capabilities to execute a certain task according to the node‘s current pheromone value. Furthermore, the strategy used by the ACO algorithm is to select the most capable node to execute each of the tasks submitted to the network. The simulations and output for the performance of the ACO algorithm were done in the Cloudsim Plus Toolkit. As a result, it indicates that the ACO algorithm is effective to achieve network load balancing and it is able to outperform the Randomized and Round Robin algorithm in all situations and settings.