Task Scheduling and Load Balancing Techniques Using Genetic Algorithm in Cloud Computing

Task scheduling and load balancing are challenging problems in cloud computing, as the demand of cloud computing resources is escalating everywhere anytime. The load on cloud nodes is very high with the increase in client request for cloud services. This condition needs load balancing techniques to uniformly distribute the client request among existing resources so that underutilization and overutilization of resources can be minimized. An impoverished scheduling strategy may over burdensome virtual machines while remaining virtual machines are idle. In this paper, load balance-aware task scheduling policy is proposed using genetic algorithm. The performance of the proposed technique is compared with existing schemes. The simulation output represents that the proposed algorithm outperforms than the current algorithms.