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Performance Analysis of Load Balancing Algorithms for cluster of Video on Demand Servers

机译:视频点播服务器集群的负载均衡算法的性能分析

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In this paper we have proposed an algorithm for a wide variety of workload conditions including I/O intensive and memory intensive loads. However, in our task the CPU requirements of the system is minimum as the tasks which come are mostly video fetch tasks which require negligible system interaction but a lot of I/O consumption. The goal of the proposed algorithm is to balance the requests across the entire cluster of servers basing on its memory, CPU and I/O requirements so that the response time and the completion time for each job is minimum. Here preemptive migrations of tasks are not taken into consideration. A typical transaction in our model can be defined as the duration between the acceptance of task into the system and fulfillment of its requirements by the system. The requirements of the task are video files which the system has to load from a secondary storage device and stream the video continuously to the end user who initiated the request. We have compared our algorithm (IOCMLB) to two other allocation policies and trace driven simulation shows that our algorithm performed better than other two policies.
机译:在本文中,我们提出了一种适用于各种工作负载条件的算法,包括I / O密集型和内存密集型负载。但是,在我们的任务中,系统的CPU需求是最低的,因为接下来的任务主要是视频获取任务,这些任务需要忽略的系统交互性,但I / O消耗很多。提出的算法的目标是根据服务器的内存,CPU和I / O需求平衡整个服务器群集中的请求,以使每个作业的响应时间和完成时间最短。此处未考虑任务的抢先迁移。我们模型中的典型事务可以定义为系统接受任务到系统满足其要求之间的持续时间。任务的要求是视频文件,系统必须从辅助存储设备加载该视频文件,然后将视频连续流式传输给发起请求的最终用户。我们将算法(IOCMLB)与其他两个分配策略进行了比较,跟踪驱动的仿真表明我们的算法比其他两个策略表现更好。

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