The Construction And Performance Analysis Of The New Regular Networks

Cloud computing technology originates in the business world before academia. These advanced technology has developed rapidly in the business world. Cloud computing has the particularity in commercial environment, these peculiarities need appropriate standards and norms. So the workflow scheduling strategy of commercial cloud environment has important theoretical and practical significance.There are two roles in commercial environment workflow scheduling. Service providers and users.This paper analyzed the quality of requirements for each roles. Users focused on the fee for the services, reduced their costs. On the other hand the providers pay more attention to saving energy consumption. In this paper, our work analyzes the problems in a business cloud environment, consider the QoS of two sides, The main work as follows:(1) To solve the problem that there are many intensive-instance service-flows in business cloud computing environment, a new two-phase service-flows scheduling algorithm is proposed. In the service-flows execution phase, in order to solve the possible problem of time exception which tasks is not meet its sub-deadline, our algorithm adjust deadlines of subsequent task dynamically. The experimental results in CloudSim shows that our algorithm compare with others algorithm save the execution cost with meeting the user-defined deadline, avoid the fierce competition of cheaper services and improves the success ratio of the scheduling.(2) In business cloud environment, there are a variety of commercial cloud services resources, those resources have different in performance and energy consumption. In this paper, we analyze the problem of energy consumption in commercial cloud environment. we establish a multi-objective optimization of energy consumption based workflow scheduling technology, these resources in terms of service performance services, energy consumption are significant differences. In this paper, these characteristics, analyzes the energy consumption in a commercial cloud environment optimization problem, we established a multi-objective optimization of energy consumption based workflow technology scheduling model, using discrete particle swarm algorithm for multi-objective optimization problem, design a new crossover operator based on to acyclic graph layers of the workflow. Those crossover unit is based on logic layers of workflows. CloudSim simulation results show that, compared with the first-come-flrst-served (FCFS) algorithm, our algorithm can better optimize the scheduling, reduce energy consumption, to provide users with multiple choice strategy to meet the different needs of users, to improve performance and achieve energy and while optimizing performance.In this paper,research on commercial cloud environment workflow scheduling strategy has achieved some results, our scheduling algorithm can better meet the needs the quality of service in commercial cloud environment, and make a balance between the user’s quality of service and level of service.Our research provide a guideline for analyzing and solving those problem in cloud computing. And play an important role in future research.