2010 · 54 citations · 9 references
Cluster ComputingEngineeringEnergy EfficiencyComputer ArchitectureData Center NetworkDatacenter-scale ComputingGreen Data CenterInternet Of ThingsEnergy ConsumptionData Center SystemComputer EngineeringData CentersData Center ArchitecturesData Center NetworkingData Center NetworksPower ConsumptionData Center ArchitectureData Center ManagementEnergy ManagementEdge ComputingCloud Computing
Data center power consumption is a major focus because it benefits both centers and the environment, yet the energy demands of the underlying architecture remain underexplored. This study analyzes how architectural parameters affect data center power use and proposes practical solutions to reduce networking energy consumption. The authors evaluate power consumption of state‑of‑the‑art topologies—BCube, DCell, and Fat‑tree—to characterize architectural impacts and inform their proposed solutions. They find that server and switch consumption issues are significant and present preliminary power results for BCube, DCell, and Fat‑tree, highlighting opportunities for energy savings.
Reducing the power consumption of data centers has recently been received much attention from the research community and the industry alike. It is because the benefits are manifold: for the data centers themselves and towards the environment. A number of issues concerning with the consumption of the servers or the switches have been investigated. However, the energy requirement of the data center architecture has not yet been sufficiently addressed. In this paper, we address this issue and make two key contributions. Before delving into the details of possible solutions for reducing power of existing data center architectures, we first characterize the impact of architectural parameters on the power consumption of data centers by presenting preliminary results on the power consumption of state-of-the-art data center structures, namely BCube [8], DCell [9], and Fat-tree [1, 11, 7]. Secondly, based on the insights and lessons learnt from the analysis, we present our vision on possible practical solutions to reduce the energy usage of data center networking.
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Albert Greenberg, James R. Hamilton, Navendu Jain et al. · 2009 · 2.1K citations
Albert Greenberg, James R. Hamilton, David A. Maltz et al. · ACM SIGCOMM Computer Communication Review · 2008 · 1.6K citations · Full text
Chuanxiong Guo, Guohan Lu, Dan Li et al. · 2009 · 1.4K citations · Full text
Cluster Computing, Engineering, High Performance Computer Network +12