PowerNap: eliminating server idle power

By David Meisner, Brian T. Gold, Thomas F. Wenisch. International Conference on Architectural Support for Programming Languages and Operating Systems, 2009

1,066 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/4aec1ba26ca8a42a041dc0ac6a43dc91f1b6abc1

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Citations in the corpus

AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers (2012, result): “This claim is also supported by recent literature [Gandhi et al. 2011b; Meisner et al. 2009, 2011].”
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment (2013, methodology): “PowerNap [23] resorts to new hardware technologies such as solid state disk (SSD) and Self-Refresh DRAM to implement rapid transition(less than 1ms) between full operation and low power state, so that it can “take a nap” in short idle intervals.”
Heracles: Improving resource efficiency at scale (2015, background): “optimizing various aspects of latency-critical workloads, including energy proportionality [53, 54, 47, 46, 34], networking performance [35, 8], and hardware-acceleration [41, 63, 72].”
A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems (2010, background): “[44] have proposed an approach for power conservation in server systems based on fast transitions between active and low-power states.”
A Survey of Green Networking Research (2010, background): “Other works such as [46], [47] provide a relative comparison of sleeping mode versus rate switch strategies, when applied to processors and servers, respectively.”
Cutting the electric bill for internet-scale systems (2009, methodology): “We use price data for 30 locations, covering January 2006 through March 2009.”
Ensuring Safety, Security, and Sustainability of Mission-Critical Cyber–Physical Systems (2012, background): “, transitioning to the sleep sate in idle times [53], [54], and active low power modes i.”
Performance Modeling and Design of Computer Systems: Queueing Theory in Action (2013, methodology): “The material in this chapter, on the M/G/1 with setup times, was applied by a former student, Brian Gold, in the well-known paper, “PowerNap: Eliminating Server Idle Power” [124].”
On the energy (in)efficiency of Hadoop clusters (2010, background): “PowerNap [ 10 ] and PCRAM, may make short inactivity periods as useful as long inactivity periods in reducing energy consumption.”
Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers (2012, background): “[42] have shown that a typical blade server consuming 450 W in the fully utilized state consumes approximately 10.”
A Survey on Green-Energy-Aware Power Management for Datacenters (2014, methodology): “The method applies a duty cycle to servers through employing rapid active active/inactive state switching via PowerNap [Meisner et al. 2009].”
Green server design: beyond operational energy to sustainability (2010, background): “3 PUE = 1+ infrastructure_power / operational_power categories of optimizations: (i) Energy proportionality (EP) [6] in the datacenter space has gained a lot of attention with several optimizations [15] [8] [29] [24] that seek to make the energy consumed by a system be proportional to the activity i”