Research on Improvement of Task Scheduling Algorithm in Cloud Computing
Wu Mingxin · Applied Mathematics & Information Sciences · 2014
In recent years, cloud computing has been focused as a new mode of service in the field of computer science. This paper starts from the definition, key technology and correspondin g characteristic that are reviewed from all the aspects of cl oud computing. As found in both literature and practice, the cloud computing face the grand quantity of the user groups, as well as the quantity of tasks and massive data, so the processing is also very significant. How to schedule tasks efficiently has become an important pro blem to be solved in the field of cloud computing. For the programming fr amework of cloud computing, a dual fitness genetic algorithm (DFGA), it can get shorter total task scheduling completion time and better results, and the results of the scheduling task avera ge completion time is also shorter. Through the simulation experiment of this algorithm, compared with other algorithms, the experimental results show that, this algorithm is better than adaptive genetic algori thm, which can be an efficient task scheduling algorithm in cl oud computing environment.