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Dynamic Multiservice Load Balancing in Cloud-Based Multimedia System

机译:基于云的多媒体系统中的动态多服务负载平衡

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摘要

Consider a centralized hierarchical cloud-based multimedia system (CMS) consisting of a resource manager, cluster heads, and server clusters, in which the resource manager assigns clients' requests for multimedia service tasks to server clusters according to the task characteristics, and then each cluster head distributes the assigned task to the servers within its server cluster. For such a complicated CMS, however, it is a research challenge to design an effective load balancing algorithm that spreads the multimedia service task load on servers with the minimal cost for transmitting multimedia data between server clusters and clients, while the maximal load limit of each server cluster is not violated. Unlike previous work, this paper takes into account a more practical dynamic multiservice scenario in which each server cluster only handles a specific type of multimedia task, and each client requests a different type of multimedia service at a different time. Such a scenario can be modelled as an integer linear programming problem, which is computationally intractable in general. As a consequence, this paper further solves the problem by an efficient genetic algorithm with an immigrant scheme, which has been shown to be suitable for dynamic problems. Simulation results demonstrate that the proposed genetic algorithm can efficiently cope with dynamic multiservice load balancing in CMS.
机译:考虑一个由资源管理器,群集头和服务器群集组成的基于云的集中式分层多媒体系统(CMS),其中资源管理器根据任务特征将客户端对多媒体服务任务的请求分配给服务器群集,然后分别群集头将分配的任务分配到其服务器群集中的服务器。但是,对于如此复杂的CMS,设计一种有效的负载平衡算法是一项研究挑战,该算法需要以最小的成本在服务器群集和客户端之间传输多媒体数据,同时将每个服务器的最大负载限制分散到服务器上,以分散多媒体服务任务负载。不违反服务器群集。与以前的工作不同,本文考虑了更实际的动态多服务方案,其中每个服务器群集仅处理特定类型的多媒体任务,并且每个客户端在不同的时间请求不同类型的多媒体服务。可以将这种情况建模为整数线性规划问题,该问题通常在计算上难以解决。结果,本文通过具有移民方案的高效遗传算法进一步解决了该问题,事实证明该算法适用于动态问题。仿真结果表明,所提出的遗传算法能够有效地应对CMS中的动态多服务负载均衡。

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