吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

异常网络环境下云计算资源需求策略

骆焦煌   

  1. 闽南理工学院 信息管理学院, 福建 泉州 362000
  • 收稿日期:2016-07-15 出版日期:2017-07-26 发布日期:2017-07-13
  • 通讯作者: 骆焦煌 E-mail:1104674880@qq.com

Strategy of Resource Demand of Cloud Computing inAbnormal Network Environment

LUO Jiaohuang   

  1. College of Information Management, Minnan University of Science and Technology, Quanzhou 362000, Fujian Province, China
  • Received:2016-07-15 Online:2017-07-26 Published:2017-07-13
  • Contact: LUO Jiaohuang E-mail:1104674880@qq.com

摘要: 针对常规云计算资源预测算法不能在异常网络环境下做到精准预测的难题, 提出一种基于改进蚁群算法的调度策略. 该策略融入了信息数的概念, 既能快速均衡负载, 又能保障用户在多条件下云计算的需要, 合理降低能耗, 提高云计算性能. 实验结果表明, 基于改进的蚁群调度算法提高了云计算资源利用率, 降低了能量消耗, 使单节点处理任务量有较大提升, 极大提高了云计算的性能和服务质量.

关键词: 异常网络, 资源调度, 云计算, 蚁群算法

Abstract: Aiming at the problem that conventional cloud computing resource prediction algorithm could not predict accurately in the abnormal network environment, the author proposed a scheduling strategy based on improved ant colony algorithm. The strategy integrated the concept of the number of information, which could not only balance load quickly, but also ensure users’ needs under multiple conditions, reduce energy consumption and improve the performance of cloud computing. The experimental results show that the improved ant colony scheduling algorithm improves the utilization of cloud computing resources, reduces energy consumption and increases task capacity for every single node, and greatly improves the performance of cloud computing and service quality.

Key words: cloud computing, ant colony algorithm, resource scheduling, abnormal network

中图分类号: 

  • TP393