SAHEFT: Security Aware Heterogeneous Earliest Finish Time Workflow Allocation Strategy for IaaS Cloud Environment

Abstract

Security is one of the most emerging issues in the real-life scientific workflow's applications such as online marketing, big data, digital transaction etc. Cloud computing infrastructure is a platform that provides dynamically scalable on demand services. However, cloud users are to pay attention to the cost incurred with pay-per-use pricing model by leasing virtual machines (VMs) from cloud centers. IT companies and scientists are facing challenges of demanded Quality of service (QoS) in IaaS cloud environment. Therefore, many researchers making effort to achieve better performance for secure workflow allocation on heterogeneous virtual machines. In this paper, a Security Aware Heterogeneous Earliest Finish Time (SAHEFT), a list-based workflow allocation strategy for single workflow to optimize guarantee ratio has been proposed for IaaS cloud environment. SAHEFT has been compared with a standard algorithm, namely HEFT, to evaluate the performance. Experimental results shows the significantly improved performance of SAHEFT over HEFT by 32.11% and 27.08% on account of security overhead and guarantee ratio respectively.