원문정보
초록
영어
Due to lacking valid prediction for resource requirement, the existing application approaches for cloud computing resource could hardly achieve a high efficiency. According to this point, we propose a mixed-prediction based resource allocation approach in this paper, which is abbreviated as MPRA. This proposed MPRA employs FFT (Fast Fourier Transform) theory to determine the cyclical attribution. If there is no such attribution existed, the Markov chain is alternatively used to predict the tendency of resource requirement. The experimental results show that the proposed MPRA could predict the future resource requirement more precisely. Moreover, based on the prediction result, it could also allocate the virtual machine resource adaptively, decrease the number of occupied physical machines, and reduce the probability of violating the SLA (Service-level Agreement).
목차
1. Introduction
2. MPRA: Mixed Prediction based Cloud Platform Resource Allocation Model
3. Resource Adaptive Allocation Algorithm
4. Experiment and Analysis
4.1. The Virtual Machine Resource Allocation Experiment
4.2. CloudSim based MPRA Simulation Analysis
5. Conclusion
Acknowledgements
References