PERFORMANCE ANALYSIS OF TASK SCHEDULING USING HYBRID GENETIC MODIFIED WHALE OPTIMIZATION ALGORITHM IN CLOUD COMPUTING

Abstract

Cloud computing plays a vital role, which is used to access computing resources and information online. There are a lot of challenges in accessing cloud computing systems. One of the major challenges among these is resource Management which includes scheduling, allocation, and sharing. In this paper, the Hybrid Genetic Modified Whale optimization algorithm which is a combined Genetic and Modified Whale optimization algorithm to analyze the performance of the cloud computing system such as task completion time, execution cost, speedup, and efficiency with proper allocation and sharing of resources The performance of the proposed algorithm is compared with Genetic algorithm and Whale optimization algorithm. The main target of this Proposed system is to reduce the completion time of the task by increasing the speed. Cloud Sim environment tool kit is used for the testing of the proposed system.

Keywords

• cloud computing
• task scheduling
• ga (genetic algorithm)
• hgmwoa (hybrid genetic modified whale optimization algorithm)