计算机应用研究2016，Vol.33Issue(10)：3011-3016,6.DOI:10.3969/j.issn.1001-3695.2016.10.032
基于仿生自主神经系统的节能高效云调度研究
Research on energy-efficient cloud scheduling based on bionic autonomic nervous systems
摘要
Abstract
For developing an efficient cloud scheduling and management mechanism taking performance and energy consump-tion into account,this paper proposed a cloud scheduling and management system based on bionic autonomic nervous systems (BANS).It presented a theoretical model for evaluating and analyzing important performance and energy consumption indexs. Then,it built a pure profit optimization model for balancing the tradeoff between performance and energy consumption.Ac-cording to theoretical analysis,this paper further adopted optimality analysis and an autonomic trigger mechanism for achieving dynamic and flexible management of local resources.Meanwhile,it developed a heuristic algorithm to obtain a global schedu-ling strategy for dispatching user requests.Experimental results illustrate the important tradeoff between performance and ener-gy consumption.It also demonstrates that the autonomic resource management can bring a significant increase of around 60%in the pure profit compared with a traditional load balance scheduling mechanism,and the global request scheduling further leads to that the pure profit raises by about 15%.关键词
云计算/仿生自主神经系统/性能/能耗/优化调度Key words
cloud computing/bionic autonomic nervous systems/performance/energy consumption/optimal scheduling分类
信息技术与安全科学引用本文复制引用
邱曦伟,邓紫璇,孙鹏,罗亮,向艳萍..基于仿生自主神经系统的节能高效云调度研究[J].计算机应用研究,2016,33(10):3011-3016,6.基金项目
国家自然科学基金资助项目（61170042）；四川省青年科技创新研究团队资助项目（2015TD0002）；中央高校基本科研业务费资助项目 （）
