研究目的
Investigating the optimal placement of geo-distributed cloud data centers, considering both cost minimization and network performance, especially in fast developing economies like China.
研究成果
The study concludes that geo-distributed cloud data centers should be planned considering both cost and performance, with adjustments for factors like delay constraints, population mobility, economic transformation, and energy structure adjustment. Centralized deployment reduces costs under less stringent delay constraints, while stricter constraints favor decentralized, smaller data centers closer to users.
研究不足
The study focuses on fast developing economies like China, and the findings may not be directly applicable to other regions. The simulation assumes certain conditions and models which may not capture all real-world complexities.
1：Experimental Design and Method Selection:
The study formulates the problem into a nonconvex quadratic optimization problem to determine the optimal placement of geo-distributed cloud data centers.
2：Sample Selection and Data Sources:
Geographic related statistics from the National Bureau of Statistics of the People’s Republic of China and network topology of ChinaNet are used.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
Simulation aims to plan geo-distributed cloud data centers with the capacity of 1 million workloads across China, considering factors like delay constraint, population mobility, economic transformation, and energy structure adjustment.
5：Data Analysis Methods:
The impact of various factors on DC placement and performance is analyzed through simulation.
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