Energy-Efficient Server Clusters

By E. Elnozahy, M. Kistler, Ramakrishnan Rajamony. Power-Aware Computer Systems, 2002

601 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/aa7e2b54b9a376f2e702392f173f0193f4cb721a

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In Electrical and Electronic Engineering

In Hardware and Architecture

In Information Systems

Citations in the corpus

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems (2016, background): “To be more specific, some of the recent research works have investigated the optimization of energy utilization by monitoring the performance virtualized ICT resources (server) and hosted workload under variable CPU frequency [19,20].”
GreenCloud: a new architecture for green data center (2009, background): “Many efforts have been made to improve the energy efficiency of IDC [9-18], including network power management [26], Chip-Multiprocessing (CMP) energy efficiency [10], IDC power capping [16], storage power management solutions [11] etc.”
Power and energy management for server systems (2004, background): “In this paper, we detail the motivation for this re earch, survey the previous work, describe a few ongoing efforts, and discuss the challenges that lie ahead.”
Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments (2010, methodology): “To reduce these costs, the use of virtualization to consolidate workloads and tune off unloaded servers has been proposed to achieve greater energy savings [3][7][18][21][24].”
The effects of energy management on reliability in real-time embedded systems (2004, background): “However, considering the huge overhead of Nming odoff a system [ 5 ], we assume that the system is always on. That is, the sleep power Pa is always consumed and is not manageable.”
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems (2008, background): “There are a number of papers that describe server or cluster level energy management using independent [18, 8] or cooperative DVS techniques [7, 11].”
Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity-Market Environment (2010, background): “While most of the new technologies have been developed aim to reduce the total power consumptions of IDCs[5], [8], [10], [18], [25], [28], [35], we are lacking a holistic approach to help better reduce the total electricity cost of IDC service providers.”
Data Center Energy Consumption Modeling: A Survey (2016, background): “where the fundamental dynamic power model described in Equation (7) was extended considering a simplification made on the system voltage [72][108].”
Memory power management via dynamic voltage/frequency scaling (2011, background): “[10] propose scaling the size of a server cluster according to load.”
An Introduction for Scientists and Engineers SECOND EDITION (2021, neutral): “[EKR03] E.”
No "power" struggles: coordinated multi-level power management for the data center (2008, methodology): “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.”
Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay Control (2007, methodology): “Elnozahy et al. present and evaluate by simulation five different power management schemes for single-tier server clusters [4].”
Energy conservation in heterogeneous server clusters (2005, methodology): “Previous work has considered request distribution optimizing both throughput and energy [10, 15, 23, 24], but in the context of homogeneous clusters.”