Ecological environment fuzzy networking system protection based on optical fiber intelligent network

Author:

Wang Kun1

Affiliation:

1. Xinyang Vocational and Technical College, College of Mathematics and Computer Science, Henan Xinyang, China

Abstract

The optical fiber network has the characteristics of providing users with wider bandwidth and supporting the changing needs of more users. At the same time, the optical fiber network can also reduce the network infrastructure investment. The traditional Ad Hoc On-demand Distance Vector (AODV) algorithm does not consider the impact of node movement on the network, and the link disconnection frequently occurs during the routing process. The ant colony algorithm based on swarm intelligence only considers the unique factor of pheromone concentration to find the optimal path through multiple iterations, which will increase the complexity of the algorithm and affect the route establishment delay. In response to the above problems, this paper proposes a routing algorithm based on fuzzy logic. The algorithm can comprehensively consider the three factors of node location, mobility and signal strength, and greatly reduces the complexity of the algorithm. This paper gives a detailed definition of profust reliability of the Ethernet Passive Optical Network (EPON) system for distribution network communication and obtains the profust reliability parameters based on Monte Carlo simulation. After that, the reliability of profust under different networking modes was simulated, and the influence of network scale, component failure rate, component repair time and other parameters on the reliability of EPON networking profust was analyzed. The fuzzy probist reliability analysis method uses analytical methods, which are commonly used to deal with end-to-end reliability analysis problems and has certain limitations. Profust reliability analysis treats the system as a whole, which is more suitable for the reliability of complex end-to-multi-end systems.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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