Open AccessDistributed Cloud Platform Access Collaborative Selection Algorithm based on Multi-objective Optimization
Author(s) -
Wei Zhao,
Huiqin Li,
Chenfei Wang,
Yajuan Wang,
Liyang Xu,
Juan Liu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/790/1/012060
Subject(s) - cloud computing , computer science , distributed computing , load balancing (electrical power) , selection algorithm , big data , grid , selection (genetic algorithm) , data mining , operating system , geometry , mathematics , artificial intelligence
Decentralization is the mainstream trend of large-scale center construction. Based on the requirements of mass service access, big data processing and high reliability of State Grid 95598 cloud platform, a distributed cloud platform access collaboration selection algorithm based on multi-objective optimization is proposed. The algorithm considers load balance of distributed cloud platform and average user experience quality. In addition, it measures the comprehensive performance of the cloud platform from users and load balance of distributed cloud platform based on the synergy degree in the selection process in order to avoid “cask effect”. The simulation results show that the algorithm can adjust the access cloud centers of users in real time and balance loads of cloud centers, which can provide technical support for cloud platform construction in the era of big data.