基于K-hop聚类算法的Ad Hoc网络局部混合数据传输方案

A. Derhab, N. Badache
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引用次数: 8

摘要

在移动自组织网络中,由于节点的自由移动,网络分区频繁发生,这大大降低了数据访问的性能。数据复制是提高移动自组织网络中数据可用性的一种很有前途的方法。在本文中,我们提出了一种结合基于推和基于拉的本地化混合数据传输方案。该方案通过实现局部聚类算法来构建组,其中每个节点与组长的距离最多为K跳。这种构造允许绑定K跳的查询访问延迟。局部聚类算法动态创建组以适应拓扑变化。它还可以预测组何时会划分。因此,它可以在分区发生之前在未来单独组的节点上复制数据项。提出的本地化方案有助于提高数据可用性,同时改善查询延迟和更新成本
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localized Hybrid Data Delivery Scheme using K-hop Clustering Algorithm in Ad Hoc Networks
In mobile ad hoc networks, as nodes move freely, network partitions occur frequently, which significantly degrades the performance of data access. Data replication is a promising approach to improve data availability in mobile ad hoc networks. In this paper, we propose a localized hybrid data delivery scheme that combines the push-based and the pull-based approaches. This scheme is constructed by implementing a localized clustering algorithm that constructs groups, in which each node is at most K hops away from a group leader. This construction permits to bind the query access delay by K hops. The localized clustering algorithm dynamically creates groups to adapt to topology changes. It can also predict when the group will partition. So, it can replicate data items on nodes of the future separate group before the partitioning occurs. The proposed localized scheme helps to increase data availability while improving query delay and update cost
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