Popularity-based polymorphic ant colony algorithm in information centric networking

Abstract

The invention discloses a popularity-based polymorphic ant colony algorithm in information centric networking. For the problems of great influence on user service quality due to lack of considering user behavior habits in a conventional ant colony routing process of CCN (Content Centric Networking), relatively high time complexity, excessively low convergence speed and premature stagnation phenomenon after search to a certain extent, the invention proposes the popularity-based polymorphic ant colony algorithm. A route decision layer is added to an upper layer of the CCN for performing operation on FIB; a network node is enabled to periodically send out explorative ants in a specific execution process; explorative ant destination selection is combined with contents popularity, so that high-popularity contents can be more updated and low-popularity contents can be less updated; and when a forwarding interface of a next hop is selected, a polymorphic ant colony forwarding policy is used; and a convergence status of node pheromone is combined with a forwarding probability, so that the ant colony convergence speed can be effectively increased and the premature stagnation is avoided.

Description

technical field [0001] The invention relates to an ant colony routing algorithm in an information center network, in particular to the design of destination selection of exploration agents, update and maintenance of optimal paths and forwarding strategies of polymorphic ant colonies. Background technique [0002] With the rapid development of Internet technology and applications, "broadband", "content" and "personalization" have become the main theme of network development. People's demand for data content is becoming stronger and stronger. Service evolution transfer. According to Cisco VNI Mobile Forecast, all content-related traffic on the Internet will account for more than 97.5% by 2014, and the traditional host-centric network architecture cannot meet the development requirements of current network information services. In order to meet the ever-increasing demand for accessing data content on the Internet, Information Centric Networking (ICN), as a revolutionary future...

AI Technical Summary

Problems solved by technology

After many iterative calculations, many ants quickly moved to paths with high pheromone concentrations, making it difficult to find those globally optimal paths with low pheromone concentrations

That is, after the search reaches a certain level, it is easy to attract ants to a suboptimal path because the pheromone of the suboptimal solution is continuously strengthened, thus causing the algorithm to converge prematurely and not obtain the real optimal solution

Accelerating the convergence speed will cause the problem that the suboptimal path is prone to stagnation, and avoiding the stagnation phenomenon will cause the defect of slow convergence speed

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