A Research of Resource Scheduling Strategy For Cloud Computing Based on Pareto Optimality M×N Production Model
as a new computing pattern for commercial application, Cloud computing makes the aggregation, selection, and sharing of geographically distributed heterogeneous resources possible to solve various of tasks including finance, engineering, science, and no matter how big the scale of those tasks are. However, it is problematic that the geographic distributed resources owned by different institutions with their different price models, usage policies and changing load. The resource providers and resource consumers have different objects, strategies, and requirement. Meanwhile, the availability of resources and the load on them dynamically varies with time. Hence, resource management in Clouds is a complicated task. An economic-based method is presented to allocate Cloud resources, which is based on Pareto optimality theory and realizes the optimal allocation of Cloud resources. And this method can largely avoid a waste of resources and achieve equilibrium between maximizing resource providers incomes and minimizing consumers paying. This paper describes a Cloud bank model that depends on market mechanism to understand deeply Pareto optimality.
Hao Li Huixi Li
School of Software Yunnan University Kunming, China School of Information Science and Engineering Yunnan University Kunming, China
国际会议
International Conference on Management and Service Science(2011年第五届管理与服务科学国际会议 MASS 2011)
武汉
英文
1-5
2011-08-12（万方平台首次上网日期，不代表论文的发表时间）