AN INTEGRATED FRAMEWORK FOR SLA-AWARE MULTI-OBJECTIVE TASK SCHEDULING IN CLOUD COMPUTING

Abstract

Cloud services are offered to consumers based on Service Level Agreements (SLAs) signed between Cloud Service Provider (CSP) and consumer. Due to on-demand provisioning of resources there is exponential growth of cloud consumers. Job scheduling is one of the areas that has attracted researchers to improve performance of cloud management system. Along with the on premise infrastructure, Small and Medium Enterprises (SMEs) also depend on public cloud infrastructure (leading to hybrid cloud) for seamless continuity of their businesses. In this context, ensuring SLAs and effective management of hybrid cloud resources are major challenging issues to be considered. Hence, there is a need for an effective scheduling algorithm which considers multiple objective functions like SLA (deadline), cost and energy while making scheduling decisions. Most of the state of the art schedulers in hybrid cloud environment considered single objective function. However, in real world, it is inadequate for scheduling effectiveness. To overcome this problem, we proposed an integrated framework which ensures SLAs (deadline), cost effectiveness and energy efficiency with an underlying scheduling algorithm known as SCE-TS. This algorithm is evaluated with different workloads and SLAs using a cloud platform. The empirical study revealed that the proposed framework improves scheduling efficiency in terms of meeting SLAs, cost and energy efficiency. It is evaluated and compared with the state of the art and found to be effective in making scheduling decisions in cloud environment.