Fault Aware BAT Algorithm for Task Scheduling in Cloud

Anant Kumar Jayswal, D. K. Lobiyal
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Abstract

Distributed resources in a cloud environment come with issues of reliability and heterogeneous performance of every data center. This behavior of the cloud comes with many issues like trust, fault, and reliability in the cloud. So, to overcome this, reliable task scheduling is required, which considers all the conduct of the cloud. In such a situation, the position, and the executives of the allocation of resources between on-premises, datacenters and cloud data centers is a fundamental problem. Distributing in the cloud places a heavy burden on the execution of the cloud and the supervision of resource and task performance. Various static and dynamic algorithms may be used to resolve this problem. For better cloud presentation in terms of several tasks failed, execution duration, and start time, a fault-aware bat algorithm inspired by undertaking distribution algorithm for cloud infrastructure is suggested in this paper.
云环境下任务调度的故障感知BAT算法
云环境中的分布式资源会带来每个数据中心的可靠性和异构性能问题。云的这种行为带来了许多问题,比如云中的信任、故障和可靠性。因此,为了克服这个问题,需要可靠的任务调度,它考虑了云的所有行为。在这种情况下,内部部署、数据中心和云数据中心之间资源分配的位置和管理人员是一个基本问题。在云中的分布给云的执行以及对资源和任务性能的监督带来了沉重的负担。可以使用各种静态和动态算法来解决这个问题。为了在任务失败数、执行时间和启动时间方面更好地呈现云,本文在云基础设施的承建分布算法的启发下,提出了一种故障感知bat算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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