Power and performance management of virtualized computing environments via lookahead control

By Dara Kusic, Jeffrey O. Kephart, James E. Hanson, Nagarajan Kandasamy, Guofei Jiang. International Conference on Automation and Computing, 2008

965 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/563f7d19eb0e7e1a7197fb498bf47263b91f8f9c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Information Systems

Citations in the corpus

An adaptive hybrid elasticity controller for cloud infrastructures (2012, methodology): “In [24], the resource-provisioning problem is posed as one of sequential optimization under uncertainty and solved using limited look-ahead control.”
Energy Efficient Allocation of Virtual Machines in Cloud Data Centers (2010, neutral): “The objective of the reallocation is to minimize the number of physical nodes serving current workload, whereas idle nodes are switched off in order to decrease power consumption.”
A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems (2010, methodology): “vironments, but not for Cloud computing providers, where more reliable QoS and a comprehensive support for SLA are essential. 8.3.3 Power and Performance Management via Lookahead Control Kusic et al. [58] have explored the problem of power and performance efficient resource management in virtualized”
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures (2010, methodology): “Recently, a number of power management systems have been proposed based on virtualization techniques, including [23], [24], [5], [25], [6], that share some adaptation methods with our approach.”
Using Ant Colony System to Consolidate VMs for Green Cloud Computing (2015, background): “Most studies [19], [31] show that CPU consumes more power than memory, disk storage, and network interface.”
Online algorithms for geographical load balancing (2012, background): “RHC is commonly proposed to control data centers [14], [15] and has a long history in control theory [16].”
Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges (2010, background): “Recent studies [28], [29], [30], [31] show that application of DVFS on CPU results in almost linear power-to-frequency relationship.”
Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers (2012, methodology): “[13] have defined the problem of power management in virtualized heterogeneous environments as a sequential optimization and addressed it using Limited Lookahead Control (LLC).”
Multi-Objective Virtual Machine Placement in Virtualized Data Center Environments (2010, background): “Paper [19][31] addresses the similar problem and proposes to measure cooling efficiency for guiding the workload placement.”
Energy Efficient Resource Management in Virtualized Cloud Data Centers (2010, positive): “Kusic et al. [8] have stated the problem of continuous consolidation as a sequential optimization and addressed it using Limited Lookahead Control (LLC).”
A survey on techniques for improving the energy efficiency of large-scale distributed systems (2014, background): “…2001; Chase et al. 2001], investigated in following works [Doyle et al. 2003; Urgaonkar et al. 2008; Verma et al. 2008; Kalyvianaki et al. 2009; Kusic et al. 2008; Jung et al. 2009; Srikantaiah et al. 2008], consists in running multiple tasks on the same physical machine in order to reduce the…”
Adaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centers (2010, methodology): “Recent studies [6] [8] show that the power consumption by servers can be accurately described by a linear relationship between the power consumption and CPU utilization, even when Dynamic Voltage and Frequency Scaling (DVFS) is applied.”
Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing (2012, methodology): “[12] have defined the problem of power management in virtualized heterogeneous environments as a sequential optimization and addressed it using Limited Lookahead Control (LLC).”
A multi-objective ant colony system algorithm for virtual machine placement in cloud computing (2013, methodology): “This technology also enables on-demand or utility computing—a just-intime resource provisioning model in which computing resources such as CPU, memory, and disk space are made available to applications only as needed and not allocated statically based on the peak workload demand [3].”