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AuthorWang, Ting
AuthorQin, Bo
AuthorSu, Zhiyang
AuthorXia, Yu
AuthorHamdi, Mounir
AuthorFoufou, Sebti
AuthorHamila, Ridha
Available date2023-04-04T09:09:12Z
Publication Date2015
Publication NameJournal of Cloud Computing
ResourceScopus
URIhttp://dx.doi.org/10.1186/s13677-015-0035-7
URIhttp://hdl.handle.net/10576/41669
AbstractThe data center network connecting the servers in a data center plays a crucial role in orchestrating the infrastructure to deliver peak performance to users. In order to meet high performance and reliability requirements, the data center network is usually constructed of a massive number of network devices and links to achieve 1:1 oversubscription for peak workload. However, traffic rarely ever hits the peak capacity in practice and the links are underutilized most of the time, which results in an enormous waste of energy. Therefore, aiming to achieve an energy proportional data center network without compromising throughput and fault tolerance too much, in this paper we propose two efficient schemes from the perspective of resource allocation, routing and flow scheduling. We mathematically formulate the energy optimization problem as a multi-commodity minimum cost flow problem, and prove its NP-hardness. Then we propose a heuristic solution with high computational efficiency by applying an AI resource abstraction technique. Additionally, we design a practical topology-based solution with the benefit of Random Packet Spraying consistent with multipath routing protocols. Both simulations and theoretical analysis have been conducted to demonstrate the feasibility and convincing performance of our frameworks. 2015, Wang et al.; licensee Springer.
SponsorThis paper is supported in part by NPRP grant from the Qatar National Research Fund and HKUST RGC Fund. Except this, the authors declare that they have no other competing interests.
Languageen
PublisherSpringer
SubjectBandwidth allocation
Data center network
Energy efficiency
Energy-aware routing
TitleTowards bandwidth guaranteed energy efficient data center networking
TypeArticle
Issue Number1
Volume Number4
dc.accessType Open Access


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