The scheduling of power transaction with Improved swarm optimization algorithm

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Wang, Lei^1^2 ; Lv, Jingwei^1^2 ; Wang, Qingbo^1^2 ; Shi, Shuhong^1^2 ; Lv, Zhenliao^3

Nari Group Corporation/State Grid Electric Power Research Institute, Nanjing

210003, China^1

Beijing Kedong Electric Power Control System Co., Ltd., Beijing

100194, China^2

Computing Center, Northeastern University, Shenyang

110819, China^3

关键词: Cloud computing environments;    Cloud computing platforms;    Minimum completion time;    Particle swarm optimization algorithm;    Power transactions;    Resource-scheduling;    Swarm optimization algorithms;    Task completion time;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/3/032084/pdf
DOI  :  10.1088/1755-1315/252/3/032084

来源: IOP

【 摘 要 】

The application characteristics of power industry are very consistent with the technology mode of cloud computing. Task and resource scheduling is one of the basic problems in the cloud computing environment. It is a big challenge to find the optimal solution in a limited time because of the large solution search space. To meet the need of the higher requirements for quality of service and response in the power trading cloud computing platform, a resource scheduling method is proposed based on Improved Particle Swarm Optimization (PSO) algorithm. Firstly, weight of particle is optimized. And then dual fitness function for particle selection strategy is proposed not only aiming at minimum completion time, but also considering quality of computing measurement. Simulation experiments show that the algorithm has a significant improvement in task completion time and resource usage.