Cloud computing is an emerging distributed, low cost computing paradigm with a large collection of heterogeneous autonomous systems. It provides, on demand, flexible and scalable services to customers through a pay per use basis. The overall performance of cloud infrastructure depends on task assignment and scheduling. Efficient task scheduling reduces power consumption of the cloud infrastructure and increase the profit of service providers by reducing processing time of the user job. This research focuses on efficient task scheduling using multi-objective Artificial Bee Colony Algorithm (TA-ABC). The proposed algorithm optimizes the energy, cost, resource utilization and processing time of the cloud environment. The results obtained by TA-ABC is also simulated by an open source cloud platform (CloudSim). Further, the proposed algorithm (TA-ABC) provide an optimal balance results for multiple objectives and the results are comparable to the state-of-the-art existing scheduling algorithms.
Sanjaya Kumar PandaPrasanta K. Jana
Sayan MukherjeeJayasree SenguptaSipra Das Bit
R JenaJ DeanS GhemawatRajkumar BuyyaaShin CheeSrikumar YeoJames VenugopalIvona BrobergBrandicS SindhuS MukherjeeY HsuP LiuJ WuY FangF WangJ GeB MondalK DasguptaP DuttaJ HuJ GuG SunT ZhaoY WeiL TianK LiG XuG ZhaoY DongD WangD KarabogaB GorkemliC OzturkN KarabogaS BitamK DebA PratapS AgarwalT Meyarivan