Managing server energy and operational costs in hosting centers

By Yiyu Chen, Amitayu Das, Wubi Qin, Anand Sivasubramaniam, Qian Wang, Natarajan Gautam. Measurement and Modeling of Computer Systems, 2005

634 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/3d078a65277681a7195c13ceeec043977b630a31

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Citations in the corpus

Resource Management in Clouds: Survey and Research Challenges (2015, background): “Work on the data center right sizing problem has continued from both algorithm development and system implementations perspectives; good examples of recent efforts are [48, 73, 106, 142].”
Dynamo: Facebook's Data Center-Wide Power Management System (2016, background): “Based on their control goals, they fall into the following groups: peak power management approaches [4], [8], [26]; thermal management approaches [9], [10], [27]; and average power or energy management approaches [28], [29], [30], [32], [33].”
GreenCloud: a packet-level simulator of energy-aware cloud computing data centers (2010, methodology): “Therefore, the power consumption of an average server can be expressed as follows [11]:”
Shares and utilities based power consolidation in virtualized server environments (2009, background): “The research community has also noticed this trend and techniques have been proposed that tradeoff performance fo r power savings [2], [9], [10], [11].”
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures (2010, methodology): “In particular, Dynamic voltage and frequency scaling of processors (DVFS) has been adopted by many authors including [14], [15], [16], [17], but mainly in single-server settings.”
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems (2008, methodology): “Resource provisioning or placement of applications on a set of physical servers to optimize the application Service Level Agreements (SLA) is a well studied problem [24, 6].”
Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services (2008, background): “Other work based on feedback and/or optimal control theory includes [6, 5, 23, 22, 16, 15], which attempt to dynamically optimize for energy, resources and operational costs while meeting performance-based SLAs.”
Server-Level Power Control (2007, background): “[11] also develop a controller to manage the response time in a server cluster.”
Hibernator: helping disk arrays sleep through the winter (2005, background): “) Other work [13], conducted in parallel with ours, also attempts to dynamically optimize energy and operational costs while meeting performance-based SLAs by using three techniques based on”
Data Center Energy Consumption Modeling: A Survey (2016, methodology): “where the fundamental dynamic power model described in Equation (7) was extended considering a simplification made on the system voltage [72][108].”
Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments (2010, background): “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].”
Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approach (2008, background): “At the data center level, some research has also been conducted to reduce computing power cost [27], [28].”
Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers (2011, methodology): “But most of them focuses on reducing energy consumption in data centers for web workloads [60] [12].”
iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator (2012, methodology): “The power consumption model is based on [8], and takes into account all the different components of a datacenter, such as chassis or”
Mobile Edge Computing (2021, background): “Any resource allocation scheme will need to balance these diverse needs of diﬀerent applications [9].”