Abstract
Cloud computing is required by modern technology. Task scheduling and resource allocation are important aspects of cloud computing. This paper proposes a heuristic approach that combines the modified analytic hierarchy process (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer methods to perform task scheduling and resource allocation. In this approach, each task is processed before its actual allocation to cloud resources using a MAHP process. The resources are allocated using the combined BATS + BAR optimization method, which considers the bandwidth and load of the cloud resources as constraints. In addition, the proposed system preempts resource intensive tasks using LEPT preemption. The divide-and-conquer approach improves the proposed system, as is proven experimentally through comparison with the existing BATS and improved differential evolution algorithm (IDEA) frameworks when turnaround time and response time are used as performance metrics.
Highlights
Cloud computing is an accelerating technology in the field of distributed computing
This section briefly describes the performance of the proposed heuristic approach
Evaluation of turnaround time To check the performance of our proposed heuristic approach, we first apply the algorithm to Cybershake seismogram synthesis and Epigenomics scientific tasks, which are described in the input data section
Summary
Cloud computing is an accelerating technology in the field of distributed computing. Cloud computing can be used in applications that include storing data, data analytics and IoT applications [1]. In the second stage, the proposed system addresses the computing resources of cloud data centers, such as CPU, memory and bandwidth using the proposed BATS+BAR optimized allocation methodology In this way, the proposed system has overcome the limitations of BATS in terms of the allocation of resources on the basis of CPU, memory and bandwidth. Preemption of the task As described in earlier sections, the proposed system ranks the tasks and allocates them as per the constraints of bandwidth and load on the virtual machine. We should check the status of the VM (i.e. whether it is free or busy)
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