Two-Stage Cloud Service Composition Optimization Algorithm and its Application Research
Aiming at the problem of providing customers with the optimal composite cloud services quickly and effectively in the current cloud service market,this paper proposes,a two-stage cloud service composition and optimization algorithm which contains gray correlation and Adaptive Genetic Algorithm.Firstly,according to the user's cloud service requirements,cloud services are screened by grey correlation analysis to form a candidate set of cloud services.Secondly,it constructs a multi-objective decision-making model of the shortest time,the minimum cost and the best availability,interoperability,scalability and satisfaction.It uses an Adaptive Genetic Algorithm to solve the model to determine the optimal cloud service composition scheme.Finally,an example is given to prove the rationality and scientificity of the algorithm in solving the optimal cloud service composition.
cloud service compositiongrey relation analysisimproved Genetic Algorithmmulti-objective decision-making