Cache method based on relative content aggregation in content-oriented network

Abstract

The invention provides a cache method based on relative content aggregation in a content-oriented network. The method comprises the cache factor strategy and the cache redundancy avoiding strategy, wherein the a cache factor enables relative content having the same content characteristics to attract one another, so that nodes cache target content more than relative content in current cache more easily, survival time of the relative content is mutually enhanced, and therefore the content having the main content characteristics in the cache will not be discarded easily; the cache redundancy avoiding strategy solves the problems that cache redundancy exists, and storage resources of the nodes are wasted. According to the cache method, popularity thought of the content and node content characteristic thought are applied to the cache scheme, therefore, under the precondition that routing performance is not affected greatly, routing expandability and routing reliability are improved, and limited cache space can be utilized more reasonably.

Description

technical field [0001] The invention relates to the cache content aggregation problem oriented to the cache scheme in the content network, in particular to the cache scheme based on the related content aggregation in the content network. Background technique [0002] In view of the fact that the existing network architecture restricts the realization of efficient content distribution functions, the content-oriented network emerges as the times require. A content-oriented network refers to a content-centric network, which uses the content name as a routing identifier, allowing users to directly access the content itself, rather than the host or server where it is located, which is the basic feature of the content-oriented network. Caching is an important factor affecting the scalability of content-oriented network routing, so the design of the cache solution is a top priority for content-oriented networks. [0003] The content-oriented network uses the content name as the ro...

AI Technical Summary

Problems solved by technology

However, the TopDown algorithm cannot make the cache closer to the user, which will increase the path length and affect the user experience

[0017] The common problem of the above schemes is that the distribution of content features in the cache is highly random, which means that there are no prominent main content features and stable feature distribution, so it is difficult to reduce the amount of routing information notified to the outside through the abstraction of content features, resulting in serious Routing Scalability Issues

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