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.
 HIGHLIGHTS
 
 Scheduling in Cloud computing has NP -Hard Problem nature that may degrades Quality of Service to users
 A Novel Sailfish optimization based scheduling algorithm (SOSA) technique is proposed to increase Quality of Service in terms of Makespan and Execution Cost
 Simulation has been performed in CloudSim on NASA workload and synthetic dataset
 Proposed SOSA techniques proves to be more effective to provide Quality of Service and proves to be more significant as compared to GA and PSO