A Novel Approach in Load Balancing for Dynamic Cloud Environment using ACO

Abstract

Cloud Computing is used to distribute and coordinate tasks in order to get optimal resource utilization and avoid overload. This proposal, present a unique method on load balancing using ant colony optimization (ACO), for workload balancing in a cloud platform. Two approaches, max-min rules and forward-backward ant mechanism are familiarized to discover the applicant nodes for load balancing. This method articulates the pheromone initialization and update affording to physical properties under the cloud environment, including pheromone vanishing, inducement, and penalty rules, etc. Combined with task execution estimation by defining the movement of ants in probability by two ways, that is, the forward movement of ant meets the backward movement of ant, or else in the adjacent node, with the goal of tracking searching processes. The proposed work provides load balancing in dynamic with high network performance.