An improved Hybrid Fuzzy-Ant Colony Algorithm Applied to Load Balancing in Cloud Computing Environment

This paper outlines a novel hybrid algorithm based on the Fuzzy logic and ant colony optimization (ACO) concepts to improve the load balancing in the Cloud environment. Unfortunately, the large number of requests processed as well as the servers available at each instant t, make the conventional algorithms of load balancing ineffective. The proposed algorithm considers the load balancing and response time objectives in the Cloud. Moreover, the performance of the ACO algorithm is strongly correlated with the ACO parameters’ values. The introduced approach (i) applies the Taguchi experimental design to identify the best value of ACO parameters (ii) and define a fuzzy module to evaluate the pheromone value in order to improve the calculation duration. The achieved simulations through CloudAnalyst platform demonstrate the effectiveness of the combined Fuzzy-ACO algorithm in comparison with other load balancing algorithms.