AN EFFICIENT LOAD BALANCING METHOD FOR CLOUD COMPUTING, BY USING IMPROVED ANT COLONY AND GENETIC METHOD

Computer Science

Computer technologies are changing day by day, different hardware’s, software’s are introducing regularly by various companies. It is quite difficult for an organization to upgrade or changed all the hardware’s and software’s other issues are related to services and maintenance. Existing load balancing Ant colony optimization can be improved by adding new parameters and combining with the Genetic algorithm. In this research we are presenting, an efficient load balancing method for cloud computing, by using improved ant colony and genetic method (Proposed IACGM). The proposed IACG method uses mainly two strategies of max-min rules and forward-backward rules for quick selection of candidate nodes. IACG also uses a new parameter of moving probability to ensure either forward and backward ants are meeting efficiently to its neighbor or not during searching. The reason behind the selection of GA is that, to ensure select only best fittest Ant in each selection period. Proposed method (IACGM) and existing (Ant Colony) methods are implemented over cloud-sim simulator and various performance measuring parameters such as makespan time, waiting time, response time and a total number of jobs migrated are calculated.

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