Reliability Analysis and Optimization of Computer Communication Network Based on Genetic Algorithm
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DOI: 10.25236/mmmce.2021.032
Author(s)
Ruiqi Peng, Shaoping Liao, Sirui Liu
Corresponding Author
Ruiqi Peng
Abstract
With the rapid development of communication network technology, especially the development of high-speed communication networks, the scale of the network is getting larger and larger, the link capacity is getting higher and higher, the link is becoming more and more sparse, and the research on network reliability is becoming more and more popular. attention. At present, network design related to system reliability constraints or goals has become a subject of many researches, and has been widely used in related fields such as communication networks, computer networks, and electrical control. The thesis first expounds the foreign research status of computer communication network reliability, as well as my country's development background, research process and reality in this field. Computer communication networks are increasingly widely used in schools, factories, enterprises, banks, transportation, energy, communications, military and other fields, ranging from people's daily life to national security and stability. Therefore, the research topic of computer communication network reliability has huge economic value, social value and social benefit. Secondly, the thesis introduces the relevant theories of computer communication network reliability, analyzes many factors that affect the reliability of computer communication network, and points out the bottleneck problem that restricts the reliability of computer communication network. On this basis, the paper puts forward a specific plan for the reliability optimization design of computer communication network, and establishes the corresponding computer communication network cost model and computer communication network reliability model. The reliability model of the communication network is solved.
Keywords
Optimization study, Computer communication, Genetic algorithm