today, cloud computing technology is becoming popular because it provides on-demand services for distributed resources like databases, servers, software, infrastructure, etc. Web traffic and service provisioning is increasing day by day. Load balancing is the biggest challenge in cloud computing, which distribute the workload dynamically across the different nodes to make sure that no node is overwhelmed or underutilized. That can be considered as an optimization problem. A good load balancing must adopt its strategy to the changing environment and the types of tasks. This paper proposes a new load balancing strategy which is based on genetic algorithm. The algorithm thrives to balancing the load of the cloud infrastructure while trying minimizing the make span of a given tasks set. The proposed load balancing policy is simulated using Cloud Analyst. The results of the simulation for sample application show that the proposed algorithm surpassed the existing algorithm like Round Robin, First Come First Serve, and Stochastic Hill Climbing.

Cloud Computing, Cloud Analyst, Load balancing, Genetic algorithm

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