Scheduling in IaaS Cloud Computing Environment using Sailfish Optimization Algorithm

Abstract

Due to the exceptional benefits of cloud computing, it has magnetized IT leaders and entrepreneurs at all levels. The cloud's popularity is attributed to various technologies like the Internet of Things (IoT), mobile computing, Fog, etc. Scheduling in cloud computing is still a challenging issue due to its NP-Hard nature. In recent years, many techniques have been proposed for optimal scheduling that can subsequently improve efficient Quality of Service (QoS). This paper has developed and analysed a novel Sailfish Optimization-based Scheduling Algorithm. SOSA is implemented on 2 data-sets; a real-world data-set from NASA workload, and a randomly generated data-set. SOSA exhibited 13.71 and 7.81 % average performance improvement in makespan compared to GA and PSO and 11.30 and 30.78 % average improvement in execution cost compared to GA and PSO.