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A Fuzzy Intra-Clustering Approach for Load Balancing in Peer-to-Peer System

机译:对等系统中的一种模糊集群内负载均衡方法

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Load balancing algorithms goal is to keep all nodes normally loaded through migration of modules from heavy loaded nodes to lightly loaded nodes. In addition, load balancing must involve low communication overhead and respond quickly to load imbalance in the system. In previous load balancing algorithms, classification of node as heavy, light or normal loaded node is done by using concept of threshold level, which is fixed and predefined. Now, today scenario is to change the status of nodes dynamically according to the state of system. So that, in this paper we proposed an algorithm for load balancing using fuzzy clustering; which improves the performance of the system without pre-defining the threshold values. The proposed algorithm is compared with other existing algorithms and is found to be fast and efficient in reducing load imbalance in Peer to Peer system.
机译:负载平衡算法的目标是通过将模块从重负载节点迁移到轻负载节点来保持所有节点正常负载。此外,负载平衡必须降低通信开销,并对系统中的负载不平衡做出快速响应。在先前的负载平衡算法中,通过使用阈值级别的概念将节点分类为重,轻或正常负载节点,该阈值级别是固定的和预定义的。现在,今天的场景是根据系统状态动态更改节点的状态。因此,本文提出了一种基于模糊聚类的负载均衡算法。无需预先定义阈值即可提高系统性能。将提出的算法与其他现有算法进行比较,发现该算法可快速有效地减少点对点系统中的负载不平衡。

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