A Hybrid Scheduling Approach in the Cloud

Abstract

The cloud has grown in wide popularity in recent years. It provides metered resources to end-users. The user gets to pay for the resource being utilized. The provision of these resources has become an issue that is to be addressed in the cloud in order to guarantee customer certification. The introduction of task scheduling will assist in curbing this issue. Has scheduling the task to the appropriate resource will guaranty users' quality of service. In this work, a hybrid genetic algorithm is being proposed. Genetic algorithm works on the basis of natural selection. The work is being validated by using computational parameters from both the user desired and provider desired criteria like time, cost, and throughput, and resource utilization. Then the proposed technique is compared to other scheduling techniques like first come first serve, short job first, and round-robin for more validity. The proposed technique has the best execution rate with a rate of 32.47 ms. The results show that the proposed hybrid GA reduces time and cost. This is a convincing technique for cloud computation.