Autonomous Data Replication Using Q-Learning for Unstructured P2P Networks

S. Thampi, K. C. Sekaran
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引用次数: 20

Abstract

Resource discovery is an important problem in unstructured peer-to-peer networks as there is no centralized index where to search for information about resources. The solution for the problem is to use a search algorithm that locates the resources based on the local information about the network. Efficient data sharing in a peer-to-peer system is complicated by uneven node failure, unreliable network connectivity and limited bandwidth. A well-known technique for improving availability is replication. If multiple copies of data exist on independent nodes, then the chances of at least one copy being accessible are increased. Replication increases robustness. In this paper, we present a novel technique based on Q-learning for replicating objects to other nodes.
基于q -学习的非结构化P2P网络自主数据复制
在非结构化点对点网络中,资源发现是一个重要的问题,因为没有集中的索引来搜索资源信息。该问题的解决方案是使用一种基于网络本地信息的搜索算法来定位资源。在点对点系统中,节点故障不均匀、网络连接不可靠和带宽有限使数据的有效共享变得复杂。提高可用性的一种众所周知的技术是复制。如果独立节点上存在多个数据副本,那么至少有一个副本可访问的可能性就会增加。复制增强了健壮性。在本文中,我们提出了一种基于q学习的新技术,用于将对象复制到其他节点。
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