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New Efficient Caching Strategy based on Clustering in Named Data Networking

机译:基于聚类的新的高效缓存策略在名称数据网络中的基础上

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The Named Data Networking NDN is one of the most proposed architecture for the new model of Internet communications based on contents distribution, called Information-Centric Network ICN. It is widely accepted by the research community since it has become dominant in ICN design that resolves TCP-IP based Internet problems such as bandwidth, delay, location dependent and congestion. Based on location host IP addresses, TCP-IP designed for Peer-to-Peer communication P2P. NDN architecture is oriented Content Centric Networking CCN, where the data is stored on routers and distributed to users from the nearest router.? Cache capacities of routers are limited compared to forwarded contents. To move from TCP-IP model to CCN model, many papers propose several new contents distribution based architecture ICN. In this paper, we propose a novel strategy to optimize the use of network resources inspired from Network clustering and cluster head selection in MANETs. Specifically, the improved K-medoids cluster algorithm is used to divide the global network in clusters, where for each cluster; three routers are selected as content routers. The first is the main caching router as well as the second and the third are the secondary caching router. The caching router selection process relies on three relevant criteria consisting of the distance between a node and its cluster centroid, the number of neighbors, and the congestion level. Two Multi Attribute Decision–Making methods MADM are applied, namely TOPSIS and AHP. Performance analysis of our proposed strategy with the established criteria showed ???its effectiveness and strong?potential.
机译:命名的数据网络NDN是基于内容分布的基于内容分布的网络通信模型最典型的架构之一,称为信息中心网络ICN。它被研究界广泛接受,因为它在ICN设计中占主导地位,可以解决基于TCP-IP的互联网问题,例如带宽,延迟,位置依赖和拥塞。基于位置主机IP地址,设计用于对等通信P2P的TCP-IP。 NDN架构是面向内容中心的网络CCN,其中数据存储在路由器上并分发给来自最近路由器的用户。与转发内容相比,路由器的缓存容量有限。要从TCP-IP模型移动到CCN模型,许多论文提出了几个新内容的基于内容的架构ICN。在本文中,我们提出了一种新颖的策略来优化从网络聚类的网络资源的使用,并在船只中的群集头选择。具体地,改进的K-METOIDS集群算法用于将全局网络划分为集群,每个群集在那里;选择三个路由器作为内容路由器。第一个是主要的缓存路由器以及第二个,第三个是辅助缓存路由器。缓存路由器选择过程依赖于三个相关标准,该标准由节点和集群质心之间的距离,邻居数量和拥塞级别组成。使用两种多属性决策方法MADM,即TOPSIS和AHP。与既定标准的拟议战略对拟议战略的绩效分析显示???其有效性和强大的?潜力。

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