Research On Data Migration Strategy Based On Artificial Fish Swarm Algorithm

In recent years, with the wide spread of Internet technology and the scale of resources in the Internet increasing rapidly, promote the continuous development of cloud computing technology and big data technology. Cloud computing is a new business computing model,it makes use of the mature virtualization technology to concentrate a large number of infrastructure resources,achieves on-demand services for the resources of data center. Different from the traditional data center,cloud data center have more scale and automation.How to effectively manage and maintain data center cloud has been widespread concern of scholars of various research areas.according to the characteristics of the cloud data center,this paper focuses on the lack of current mainstream cloud data migration strategy exists, especially in load balancing and bandwidth bottlenecks, etc. Through in-depth study and summary of the cloud data migration strategy, proposed a data migration strategy based on improved artificial fish swarm algorithm IAFA.Data migration is a key part of the data system integration to ensure system upgrade and update smooth. It also plays an important role in cloud computing.The quality of data migration is not only an important presupposition of the appliance for the new system but also a guarantee of the stable operation for the system. In this paper, the experiment is done on the autonomous cloud computing. Data migration strategy is applied in the autonomous cloud computing system to optimize and improve the performance of the service for cloud computing. The effective implementation of the dynamic migration strategy and autonomy is a important part of the paper.The main idea of IAFA is divided into two parts:First of all, based on the artificial fish swarm algorithm and the design of each physical server load objective function for global search, and introduces the adaptive inertia weight to avoid individual artificial fish into local optimum. Secondly,search for the optimal solution of this process on a target function constraints limit, making for the optimal solution in the aspect of load balance and bandwidth utilization is the optimal solution. Finally, the experimental results show that compared with the existing migration policies, the IAFA algorithm can find a more suitable for the goal of data migration, scattered in the I/O operations at the same time to optimize the data access speed, and improve the server resource utilization and bandwidth utilization. To solve the problem of cloud data center of bandwidth bottlenecks, to ensure the transparent cloud data center services and run efficiently.This paper applied the cloud computing simulation platform Cloud Sim,and carry on the simulation with the algorithm proposed in preceding text.The paper has studied Cloud Sim resource allocation mechanism,realized resource allocation simulation program of optimization algorithm and IAFA algorithm on the Cloud Sim platform, the result of experiments prove the validity of IAFA.