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Achieving Energy Efficiency in Data Centers Using an Artificial Intelligence Abstraction Model

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Today’s data center networks are usually over-provisioned for peak workloads. This leads to a great waste of energy since in practice traffic rarely ever hits peak capacity resulting in the… Click to show full abstract

Today’s data center networks are usually over-provisioned for peak workloads. This leads to a great waste of energy since in practice traffic rarely ever hits peak capacity resulting in the links being under-utilized most of the time. Furthermore, the traditional non-traffic-aware routing mechanisms worsen the situation. From the perspective of resource allocation and routing, this paper aims to implement a green data center network and save as much energy as possible. With the benefit of blocking island paradigm, we present a general framework trying to maximize the network power conservation and minimize sacrifices of network performance and reliability. The bandwidth allocation mechanism together with power-aware routing algorithm achieve a bandwidth guaranteed green tighter network. Moreover, our fast efficient heuristics for allocating bandwidth enable the system to scale to large sized data centers. The evaluation result shows that achieving up to more than 50 percent power savings are feasible while guaranteeing network performance and reliability.

Keywords: efficiency data; network; energy; achieving energy; energy efficiency; data centers

Journal Title: IEEE Transactions on Cloud Computing
Year Published: 2018

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