Research On Adaptive Evolution Of Service Based On QoS Under Cloud Computing Environment

With the rise of cloud computing technology, services are growing in an explosive way. more and more people are using cloud services in both life and work, cloud services have become the mainstream trend of IT services. The cloud computing environment is dynamic and open, so the user needs also frequent changes, in order to adapt to the open cloud computing environment, cloud services need to be a certain adaptive evolution.Due to the continued availability, cloud service evolution has become the focus of current research, but in the current study, few studies on cloud services adaptive evolution, in the small number of studies, with little regard for the quality of service(QoS of service,QoS).In view of the above problems, this paper takes the cloud services as the research object, and regard QoS as assessment criteria, mainly studies the adaptive evolution of cloud services and the service selection in the evolution process. First of all, taking into account in the cloud adaptive evolution, often appear the context information(demand information) changes related to the definition of adaptive problems, to explore and describe for cloud computing and its quantitative evaluation standard formula of QoS service environment, then gives the specific adaptive evolution framework and consider to optimize process service exception information, combined with the adaptive evolution framework for operation in the evolution process, adaptive evolution and operation strategy, and put forward the adaptive evolutionary algorithm, the algorithm considering the Qo S evaluation standard is described in this paper, in order to ensure the evolution of services to meet the needs of users. Secondly, in adaptive evolution process in cloud service selection problem, first to the service were pre classification processing, reduce the optimization time, analysis of cloud services in the computational expressions for the four combinations of basic structure of Qo S and problem is converted into a cloud serviceoptimization multi-objective programming problem, and the combination of particle swarm estimation of distribution algorithm framework, and proposed a hybrid particle swarm algorithm for solving the problem. Finally, the simulation analysis was carried out on these issues, mainly verifies the effectiveness and efficiency of the verification and comparison of the proposed algorithm, and the experimental results are analyzed, the algorithm has certain advantages for the efficiency.This paper propose an adaptive evolutionary algorithm and a service selection algorithm in the adaptive evolution of cloud services, the operation of cloud services is more reasonable, to improve the overall service Qo S value, According to the demand change of adaptive evolution, not only can real-time and effectively meet the needs of users, but also greatly improve the accuracy and efficiency of adaptive evolution.