Load Balancing of Distributed Systems Based on Multiple Ant Colonies Optimization

Abstract

Problem statement: Ant Colony Optimization (ACO) provides a meta-heuristic optimization tool and collective intelligence model to several applications such as routing and load balancing. A lot of work found in the literature on using ACO in load balancing. However, as far as our knowledge, there was no work relating load balancing in distributed systems with ACO. Approach: In this study, a proposed ACO algorithm for load balancing in distributed systems will be presented. This algorithm is fully distributed in which information is dynamically updated at each ant movement. Multiple colonies paradigm will be adopted such that each node will send a colored colony throughout the network. Results: In this study, colored ant colonies are used to prevent ants of the same nest from following the same route and hence enforcing them to be distributed all over the nodes in the system and each ant acts like a mobile agent that carries newly updated load balancing information to the next visited node. Conclusion: Finally, the performance of the proposed ACO algorithm is compared with the work-stealing approach for load balancing in distributed systems.