Applied Mathematics & Information Sciences

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Scheduling plays an important role in cloud computing to achieve effective load balancing by migrating tasks to partially utilized Virtual Machines (VMs). This sharing of resources provides effective scheduling in which non preemptive tasks are irretrievable constraints in cloud computing environment. Therefore, these non preemptive tasks should be initially allocated to the most suitable VMs itself. Basically, each jobs entering comprises of several interconnected tasks which may be executed by multiple VMs or different cores of a single VM. Moreover, the jobs are arrived during the server run time at random time intervals with different load conditions. In order to provide efficient cloud computing, static or dynamic scheduling techniques are used to allocate the tasks to the suitable resources and by which the involved heterogeneous resources are organized. Hence, the user satisfaction is improved. In this paper, a Novel and Adaptive Enhanced Round Robin (NAERR) algorithm is proposed which computes the size and length of all requesting jobs, the capabilities of all available VMs, and the interconnection among the tasks. The proposed and existing techniques are compared to prove the performance of the proposed algorithm.

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