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A Fuzzy Grouping-Based Load Balancing for Distributed Object Computing Systems

机译:用于分布式对象计算系统的基于模糊分组的负载平衡

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In the distributed object computing systems a set of server objects are made available over the network for computations on behalf of remote clients. In a typical distributed system setting the existing load balancing algorithms usually do not consider the global system state. In this paper we propose a new approach for improving the performance of distributed system using fuzzy grouping-based load balancing. It utilizes membership graphs in terms of the amount of CPU time and memory used for inferencing the service priority. Extensive computer simulation reveals that the proposed approach allows consistently higher performance than other approaches in terms of response time and throughput for various number of servers and tasks.
机译:在分布式对象计算系统中,通过网络提供一组服务器对象,以代表远程客户端计算计算。在典型的分布式系统中,设置现有负载平衡算法通常不考虑全局系统状态。在本文中,我们提出了一种采用模糊分组负载平衡提高分布式系统性能的新方法。它根据用于推断服务优先级的CPU时间和内存量而使用隶属关系图。广泛的计算机仿真显示所提出的方法允许与各种服务器和任务的响应时间和吞吐量方面的性能始终如一的性能。

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