云计算
计算机科学
数据中心
可靠性(半导体)
整数规划
同步(交流)
虚拟化
缩小
总成本
分布式计算
运筹学
计算机网络
操作系统
业务
频道(广播)
工程类
会计
物理
功率(物理)
程序设计语言
量子力学
算法
作者
Takashi Kurimoto,Shigeo Urushidani,Eiji Oki
标识
DOI:10.1109/tnsm.2018.2873831
摘要
We propose an optimization model for designing multiple network functions virtualization (NFV)-based campus area networks (CANs). Organizations, such as universities and research institutions have their own campus information and communication technology equipment, but many would like to move this equipment to NFV and cloud data centers for improving reliability and resiliency. However, NFV-based CAN is not affordable for them, because costs are higher with a cloud. One solution is for multiple organizations to procure NFV and cloud data center resources together. By doing so, their individual costs of using these resources will be reduced. To make progress on this approach, there are planning issues to resolve when choosing optimal NFV and cloud data center locations. The proposed model minimizes the total network costs incurred by the organizations, including the wide area network cost and data synchronization costs for recovery from faults at data centers and the various subcampus network configurations of legacy CANs. The model is formulated and analyzed by using mixed integer linear programming. The effect of cost minimization is evaluated in a ladder network and an actual network, SINET5, and it is found that the costs can be reduced by up to 63%. The calculation times of this model under practical conditions are short and the model will be useful in practice. It is also shown that the cost of fault recovery can be suppressed. These results will encourage organizations to deploy NFV-based CANs.
科研通智能强力驱动
Strongly Powered by AbleSci AI