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Virtual Machine-Based Task Scheduling Algorithm

V Karthickbalaji, L Sadaiyappan, S Sivasubramaniam, D kalaiselvi

Abstract


Cloud computing is a type of internet-based computing that provides shared computer processing resources and other devices on demand. It is very useful for the applications which sharing their resource on different nodes and also cloud computing has more scalability. The performance and efficiency of cloud computing always depends on the performance of user tasks. Virtualization concept was introduced to improve the efficiency of cloud computing. Virtualization refers to creating a virtual (rather than actual) version of something. Virtualization technology mainly used to virtualize single server to multiple server in cloud computing platform. In cloud computing the load balancing concepts are classified into three types such as data center selection, virtual machine scheduling and task scheduling. Task scheduling plays a key role in cloud computing systems. Scheduling in cloud is responsible for selection of best suitable resource for task execution. Task scheduling methods of cloud computing considering the task resource requirement of CPU and memory without considering bandwidth requirement. In the existing cloud computing environment, most of the tasks scheduling-based algorithms are used. Bandwidth and data transmission are not considered in the existing system. In the proposed system, we are introducing a Quantum Particle Swarm Optimization which is used to solve task scheduling problem with bandwidth and data transmission parameters. The proposed algorithm is simpler and more powerful than the algorithms already existing. It will exhibit minimization of makespan, computation cost, communication cost and the bandwidth to improve the data transmission rate.

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References


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DOI: https://doi.org/10.37628/ijosct.v3i1.240

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