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A Fair-Rank Ant Colony Algorithm in Distributed Mass Storage System

机译:分布式大容量存储系统中的蚁群算法

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In general, a distributed mass storage system is composed of a large number of computing nodes and storage nodes, allowing users to access resources transparently, without knowing where the resources are physically located. For every storage request, the storage system scheduler chooses several storage nodes from the entire storage system in order to organize a substorage system. This kind of scheduling is an NP-hard problem; to achieve the storage system’s promising potential, this paper proposes a virtual subsystem quality of service scheduling model and a fair-rank ant colony algorithm. The algorithm provides special incentives to the scheduling results that include new nodes, so the new nodes will have more opportunities to participate in the scheduling system. Tests show that this algorithm performs better in the fairness and load balance than the ant colony algorithm.
机译:通常,分布式海量存储系统由大量计算节点和存储节点组成,允许用户透明地访问资源,而无需知道资源的物理位置。对于每个存储请求,存储系统调度程序都会从​​整个存储系统中选择几个存储节点,以组织一个子存储系统。这种调度是一个NP难题。为了实现存储系统的巨大潜力,本文提出了虚拟子系统服务质量调度模型和公平蚁群算法。该算法对包括新节点的调度结果提供了特殊的激励,因此新节点将有更多机会参与调度系统。测试表明,该算法在公平性和负载均衡方面比蚁群算法有更好的表现。

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