Publication | Closed Access
No "power" struggles
621
Citations
24
References
2008
Year
Unknown Venue
Cluster ComputingHeat ManagementEngineeringData Center EnvironmentsComputer ArchitectureSocial ChangePower RelationGreen Data CenterPower IndexSystems EngineeringLanguage StudiesPower-aware SoftwareData Center SystemComputer EngineeringData CentersCritical TheoryPolitical PowerSmart GridEnergy ManagementCloud ComputingCrisis ManagementPower-efficient Computing
Data center power delivery, electricity consumption, and heat management are increasingly critical, yet existing solutions address only isolated aspects and lack coordination, risking unpredictable interference. The study aims to coordinate disparate power‑management techniques to mitigate interference and improve data center efficiency. The authors develop a unified architecture that coordinates individual approaches, validate its correctness and stability through simulation, and conduct a detailed sensitivity analysis of architectural, implementation, workload, and design factors. Simulations on 180 server traces from nine enterprises confirm the solution’s correctness, stability, and efficiency gains.
Power delivery, electricity consumption, and heat management are becoming key challenges in data center environments. Several past solutions have individually evaluated different techniques to address separate aspects of this problem, in hardware and software, and at local and global levels. Unfortunately, there has been no corresponding work on coordinating all these solutions. In the absence of such coordination, these solutions are likely to interfere with one another, in unpredictable (and potentially dangerous) ways. This paper seeks to address this problem. We make two key contributions. First, we propose and validate a power management solution that coordinates different individual approaches. Using simulations based on 180 server traces from nine different real-world enterprises, we demonstrate the correctness, stability, and efficiency advantages of our solution. Second, using our unified architecture as the base, we perform a detailed quantitative sensitivity analysis and draw conclusions about the impact of different architectures, implementations, workloads, and system design choices.
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