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An Adaptive Task Scheduling Method for Networked UAV Combat Cloud System Based on Virtual Machine and Task Migration

机译:基于虚拟机和任务迁移的联网UV战斗云系统自适应任务调度方法

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This paper presents a systematic work aiming to improve the efficiency of task processing in a networked UAV combat cloud system. The work consists of three major aspects: (1) an architecture of UAV combat cloud systems—such a system provides the necessary resource pool for powerful computing and storage facilities and defines the attributes of the entities in the resource pool in detail; (2) an online adaptive task redistribution and scheduling algorithm—the algorithm involves task migration being performed on virtual machines on the cloud system and aims to address the problems caused by static task scheduling approaches; and (3) an online virtual machine and task migration algorithm—the algorithm considers collectively the priority type and quantity of the tasks to be migrated on virtual machines along with time constraints to determine the migration of virtual machine or task and optimize resource usages. Experimental simulation results have demonstrated that the proposed system and the relevant algorithms can significantly improve the efficiency of task schedule.
机译:本文介绍了一个系统的工作,旨在提高网络UV战斗云系统中的任务处理效率。这项工作包括三个主要方面:(1)UAV战斗云系统的体系结构 - 这种系统为强大的计算和存储设施提供了必要的资源池,并详细描述了资源池中的实体属性; (2)在线自适应任务重新分配和调度算法 - 算法涉及在云系统上的虚拟机上执行任务迁移,并旨在解决静态任务调度方法引起的问题; (3)在线虚拟机和任务迁移算法 - 算法统称地认为要在虚拟机上迁移的任务的优先级类型和数量以及时间约束,以确定虚拟机或任务的迁移并优化资源用量。实验模拟结果表明,所提出的系统和相关算法可以显着提高任务时间表的效率。

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