Micro-cloud deployment method based on improved cuckoo search algorithm

Abstract

The invention provides a micro-cloud deployment method based on an improved cuckoo search algorithm. According to the method, a discrete cuckoo search algorithm and a discrete differential evolution algorithm are combined together, in a first stage, the position of a cuckoo population is updated through a discrete Levy flight mechanism, individuals with the maximum fitness in each generation of population are directly reserved to the next generation, and the individuals are prevented from being damaged by crossover and mutation operation; in a second stage, nest loss operation of the cuckoo algorithm is improved through a discrete differential evolution algorithm, a small part of inferior gene individuals in the first stage are evolved through mutation operators and excellent parent genes,and the convergence rate of the algorithm is increased while excellent genes of a population are reserved and the diversity of the population is increased. The algorithm is high in solving speed, thepermanent deployment position of the micro-cloud can be solved in a short time in a large-scale Internet-of-things network, the use efficiency of the micro-cloud in the network is greatly improved, and the service life of the micro-cloud in the network is greatly prolonged.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, relates to the field of edge computing and optimization, and specifically designs a micro-cloud deployment method based on an improved cuckoo search algorithm. The invention can solve the permanent deployment position of the micro-cloud in a short time, and greatly improve the use efficiency and lifespan of the micro-cloud in the network. Background technique [0002] With the advent of the Internet of Everything era, the linear growth of centralized cloud computing capabilities cannot match the exponential growth of data generated by network edge terminals, and massive data access to cloud computing centers at the network edge will consume a very large network bandwidth and generate a lot of data. High network latency. Faced with this dilemma, edge computing, as a new computing model, builds a bridge between IoT devices and data centers, and data is processed in a timely and efficient m...

AI Technical Summary

Problems solved by technology

Some scholars at home and abroad have done some research in this area, but seldom apply this algorithm to solve the location of deploying micro-clouds

In addition, the existing cuckoo search algorithm is prone to premature maturity in the later stage of evolution, and it is easy to fall into a local optimal solution, resulting in the inability to search for a global optimal solution, which also limits its application in micro-cloud deployment

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