期刊
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
卷 19, 期 2, 页码 1306-1320出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2022.3147247
关键词
Data centers; Bandwidth; Cloud computing; Optimization; Delays; Data models; Computational modeling; Cloud data center; data and service evacuation; disaster; early warning time
资金
- National Natural Science Foundation of China [61702068]
- Academic Funding Project for Top Talents of Disciplines (Majors) in Universities of Anhui Province of China [gxbjZD2021080]
- Key Natural Science Project in Universities of Anhui Province of China [KJ2020A0718, KJ2021ZD0128, KJ2021ZD0129]
This paper proposes a joint data and service evacuation scheme for emergency protection in cloud data centers, by exploiting the early warning time and designing time-efficient heuristics. Extensive numerical results demonstrate its efficiency in improving the survivability of data and services.
As important network infrastructures to support data storage and service delivery for worldwide users, cloud data centers are facing great threaten by frequent disasters around the world and thus the survivability of cloud data centers becomes a critical issue. Since both data and service evacuations are desired at the same time under a real disaster scenario, this paper studies a joint design of them to fight against disasters. We consider a disaster that can present an early warning time before it really affects cloud data centers, and by exploiting the intrinsic interplay between data and service evacuations and efficiently utilizing the early warning time we propose a joint data and service evacuation scheme for emergency protection. We first formulate the joint design as two optimal Integer Linear Program (ILP) models. Notice that the protection process is highly time-sensitive due to the early warning time constraint, two time-efficient heuristics are then designed by carefully selecting evacuated services and candidate evacuation nodes to achieve a better sharing of network resources between data backup and service migration. Extensive numerical results demonstrate the efficiency of the proposed scheme on improving survivability of data and services in cloud data centers. With a set of given resource and early warning time constraints, this work can guide data center operators to achieve a tradeoff between data backup and service migration.
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