Adaptive Skip Graph Framework for Peer-to-Peer Networks: Search Time Complexity Analysis

Amit Goyal, Shalini Batra, Neeraj Kumar, G. Aujla, M. Obaidat
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引用次数: 4

Abstract

With the enormous growth of number of nodes in a peer-to-peer (P2P) network, establishing a direct connection between two communicating nodes is a challenging task. It is mandatory to have a strong connection between different nodes for data sharing among P2P networks. Hence, this paper presents a modified data structure, named as Adaptive Skip Graph, a variant of a probabilistic data structure, skip list, which establishes a direct connection between two frequently communicating nodes by changing the membership vector of the caller node once the threshold is crossed. The proposed approach reduces the search time complexity of skip graph (O(log n)) substantially for the scenario where a node 'x' is repeatedly queried by a certain node 'y'. The results obtained using the proposed scheme are validated by experiments performed on a large set of nodes.
对等网络的自适应跳图框架:搜索时间复杂度分析
随着P2P网络中节点数量的急剧增长,在两个通信节点之间建立直接连接是一项具有挑战性的任务。为了在P2P网络中共享数据,不同节点之间必须有牢固的连接。因此,本文提出了一种改进的数据结构,称为自适应跳跃图(Adaptive Skip Graph),它是概率数据结构跳跃表的一种变体,它通过在跨越阈值时改变调用方节点的隶属向量,在两个频繁通信的节点之间建立直接连接。对于节点“x”被节点“y”重复查询的情况,该方法显著降低了跳跃图的搜索时间复杂度(O(log n))。在大量节点上进行的实验验证了该方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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