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An improved task scheduling and load balancing algorithm under the heterogeneous cloud computing network

机译:异构云计算网络下的一种改进的任务调度与负载均衡算法

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In recent decades, with the rapid development and popularization of Internet and computer technology, cloud computing had become a highly-demanded service due to the advantages of high computing power, cheap cost of services, scalability, accessibility as well as availability. However, a fly in the ointment was that the system is more complex while dispatching variety of tasks to servers. It means that dispatching tasks to the servers is a challenge since there has a large number of heterogeneous servers, core and diverse application services need to cooperate with each other in the cloud computing network. To deal with the huge number of tasks, an appropriate and effective scheduling algorithm is to allocate these tasks to appropriate servers within the minimum completion time, and to achieve the load balancing of workload. Based on the reasons above, a novel dispatching algorithm, called Advanced MaxSufferage algorithm (AMS), is proposed in this paper to improve the dispatching efficiency in the cloud computing network. The main concept of the AMS is to allocate the tasks to server nodes by comparing the SV value, MSV value, and average value of expected completion time of the server nodes between each task. Basically, the AMS algorithm can obtain better task completion time than previous works and can achieve loadbalancing in cloud computing network.
机译:在最近的几十年中,随着Internet和计算机技术的迅速发展和普及,云计算由于具有强大的计算能力,低廉的服务成本,可伸缩性,可访问性和可用性等优点而成为一项需求量很大的服务。然而,美中不足的是,该系统在向服务器分派各种任务时更加复杂。这意味着将任务分配到服务器是一个挑战,因为存在大量的异构服务器,因此核心和多样化的应用程序服务需要在云计算网络中相互协作。为了处理大量任务,一种适当而有效的调度算法是在最短的完成时间内将这些任务分配给适当的服务器,并实现工作负载的负载平衡。基于上述原因,本文提出了一种新的调度算法,称为高级MaxSufferage算法(AMS),以提高云计算网络中的调度效率。 AMS的主要概念是通过比较SV值,MSV值和每个任务之间服务器节点的预期完成时间的平均值,将任务分配给服务器节点。基本上,AMS算法可以比以前的工作获得更好的任务完成时间,并且可以在云计算网络中实现负载平衡。

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