Quaternion-Based Iterative Solution of Three-Dimensional Coordinate Transformation Problem Huaien Zeng and Qinglin Yi Modeling and Simulation on Dynamic Allocation and Scheduling of Multi-resource Problem
نویسندگان
چکیده
Resource management is one of the main issues in Cloud Computing. In order to improve resource utilization of large Data Centers while delivering services with higher QoS to Cloud Clients, an automatic resource allocation strategy based on market Mechanism (ARAS-M) is proposed. Firstly, the architecture and the market model of ARAS-M are constructed, in which a QoS-refectitive utility function is designed according to different resource requirements of Cloud Client. The equilibrium state of ARAS-M is defined and the proof of its optimality is given. Secondly, A Genetic Algorithm (GA)-based automatic price adjusting algorithm is introduced to deal with the problem of achieving the equilibrium state of ARAS-M. Finally, ARAS-M is implemented on Xen. Experiment results show that ARAS-M can approximately achieve the equilibrium state, that is, demand and supply is nearly balanced, which validates that ARAS-M is effective and practicable, and is capable of achieving resource balance in cloud computing.
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