A Multi-Objective Cat Swarm Optimization Algorithm for Workflow Scheduling in Cloud Computing Environment

摘要

As the world is progressing towards faster and more efficient computing techniques, cloud computing has emerged as an efficient and cheaper solution to such increasing and demanding requirements. Cloud computing is a computing model which facilitates not only the end-users but also organizational and other enterprise users with high availability of resources on demand basis. This involves the use of scientific workflows that require large amount of data processing which can be costly and time-consuming if not properly scheduled in cloud environment. Thus, scheduling has a great impact on both cloud service providers and users. A properly scheduled service benefits both parties. Various scheduling strategies have been developed which include swarm-based optimization approaches as well. Due to the presence of multiple and conflicting requirements of users, multi-objective optimization techniques have become popular for workflow scheduling. This study deals with Cat-swarm based multi-objective optimization approach to schedule workflows in cloud computing environment. The objectives considered are minimization of cost, makespan and CPU idle time. Researchers have implemented this technique and compared the experimental results with existing Multi-Objective Particle Swarm Optimization (MOPSO) technique and have obtained improved performance.