Cloud resource allocation as non-preemptive approach

The increased amount of data and increased degree of connectivity has led many providers to provide cloud services. One of the Cloud Services Infrastructure as a Service (IaaS), provides greater potential for a highly scalability of computing resources for demand in various applications like Parallel Data processing. The resources offered in the cloud are probably heterogeneous and extremely dynamic and due to this dynamic access balancing, load balancing and scheduling of job is required. For achieving this many schemes are proposed, Nephele is one of the data processing framework which exploits the dynamic resource allocation offered by IaaS clouds for both task scheduling and execution. Specific tasks of processing a job can be allotted to different types of virtual machines which are automatically instantiated and terminated during the job execution. However the current algorithms are homogeneous and they do not consider the underutilization or resource overload during the job execution that increases task completion time. For increasing the efficiency of the scheduling algorithm for the real time Cloud Computing services, this paper introduces a new approach. Proposed method utilizes the Turnaround time Utility efficiently by discriminating it into a gain function and a loss function for a single task based on their priorities. Algorithm has been executed on both preemptive and Non-preemptive methods. The experimental results show that it overtakes the existing utility based scheduling algorithms and also compare its performance with both preemptive and Non-preemptive scheduling approaches. Hence, Turnaround time utility scheduling approach which focuses on both high and the low priority jobs that arrives for scheduling is proposed.