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Online Bicriteria Load Balancing Using Object Reallocation

机译:使用对象重新分配的在线Bicriteria负载平衡

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摘要

We study the bicriteria load balancing problem on two independent parameters under the allowance of object reallocation. The scenario is a system of $M$ distributed file servers located in a cluster, and we propose three online approximate algorithms for balancing their loads and required storage spaces during document placement. The first algorithm is for heterogeneous servers. Each server has its individual tradeoff of load and storage space under the same rule of selection. The other two algorithms are for homogeneous servers. The second algorithm combines the idea of the first one and the best existing solution for homogeneous servers. Using document reallocation, we obtain a smooth tradeoff curve of the upper bounds of load and storage space. The last one bounds the load and storage space of each server by less than three times of their trivial lower bounds, respectively; and more importantly, for each server, the value of at least one parameter is far from its worst case. The time complexities of these three algorithms are $O(log M)$ plus the cost of document reallocation.
机译:在对象重新分配的允许下,我们研究了两个独立参数上的双标准负载平衡问题。该方案是一个位于群集中的$ M $分布式文件服务器系统,我们提出了三种在线近似算法,用于平衡文档放置期间的负载和所需的存储空间。第一种算法适用于异构服务器。在相同的选择规则下,每个服务器都有各自的负载和存储空间权衡。其他两种算法适用于同类服务器。第二种算法结合了第一种算法的思想和同类服务器的最佳现有解决方案。使用文档重新分配,我们获得了负载和存储空间上限的平滑折衷曲线。最后一个限制每个服务器的负载和存储空间分别不到其下限的三倍;更重要的是,对于每台服务器,至少一个参数的值远不是最坏的情况。这三种算法的时间复杂度为$ O(log M)$加上文档重新分配的成本。

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