Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i4/80553
Year: 2016, Volume: 9, Issue: 4, Pages: 1-10
Original Article
Indukuri R. Krishnam Raju1*, Penmasta Suresh Varma1 , M. V. Rama Sundari2 and G. Jose Moses3
1Department of Computer Science and Engineering, Adikavi Nannaya University, Rajahmundry - 533296, Andhra Pradesh, India; [email protected], [email protected] 2Department of Computer Science and Engineering, ISTS College of Engineering, Rajahmundry – 533294, Andhra Pradesh, India; mvramasu[email protected] 3Department of Computer Science and Engineering, Rahgu Engineering College, Visakhapatnam - 531162, Andhra Pradesh, India; [email protected]
*Author For Correspondence
Indukuri R. Krishnam Raju
Department of Computer Science and Engineering, Adikavi Nannaya University, Rajahmundry - 533296, Andhra Pradesh, India;
Email: [email protected]
Background/Objectives: Cloud computing is a large-scale distributed computing paradigm in which a pool of abstracted, virtualized, dynamically-scalable resources such as computing power, storage, platforms and services are delivered on demand to external customers over the Internet. In cloud computing scheduling is the process of deciding how to allocate resources in the form of virtual machines for the requested jobs. Methods: The proposed Deadline Aware Two Stage Scheduling in cloud computing is to schedule Virtual Machines (VM) for the requested jobs received from customers. In this model each job requires two types of VM’s in a sequence to complete its task. This model allocates VM’s as resource to the requested jobs based on processing time and scheduling the jobs by considering deadlines with respect to response time and waiting time. Findings and Improvements: A simulation environment was developed and analyzed to evaluate this model by considering the evaluation metrics of average turnaround time, average waiting time and violation in deadlines when compared with First Come First Serve (FCFS) and Shortest Job First (SJF) scheduling strategies. This model reduces the evaluation metrics by constant factor when compared with other scheduling approaches.
Keywords: Cloud Computing, Resource Allocation, Two Stage Scheduling, Virtual Machine
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