Hybridization of Computational Intelligence Algorithm for Scheduling of Tasks and Balancing of Load in Cloud Network

Cloud computing is a network framework that acts as a delivery of many computing resources over the internet to cloud users. During the course, cloud computing faces many challenging issues in balancing the distribution of workload among the virtual machines (VMs). The major problem that should never occur during the access of cloud resources is a physical host or VMs should never be either overloaded or underloaded. Due to this, they are more prone to system crashes or the processing time gets delayed by degrading the cloud performance. Therefore, it is required to define a load balance module over the cloud network, so that the VMs will be in balanced state. To carry out this work, proposed a novel improved (ISCA) over a single objective optimization problem. The algorithm is named as ITSA-ISCA. The proposed model to bring out degree of balance among VMs based on execution time, makespan, and resource utilization. The performance evaluation is carried out using cloudsim simulation tool of version 3.0.3. The results of simulation prove that the proffered hybrid ITSA-ISCA is supercilious compared to its competitor algorithms by maintaining a proper balance between intensification and diversification and also by maximizing utilization of resources and minimizing the execution time and makespan.