A Robust Energy-Efficient Framework for Heterogeneous Datacenters

Manakul, Kittituch; See, Simon; Achalakul, Tiranee

doi:10.1007/978-3-642-27180-9_43

Cited by 1 publication

(6 citation statements)

References 8 publications

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“…In this paper, we extend the work in [4] to design the PSG module. The main task of PSG is to determine a set of suitable computers for each process in a data center.…”

Section: Energy-efficiency-based Placement Scheme Generationmentioning

confidence: 98%

“…The general idea is described in Fig.1. PSG requires process and machine profiles [4]. Process profile describes the resource usage behavior of each process during a time slot, T SLOT .…”

Section: Energy-efficiency-based Placement Scheme Generationmentioning

confidence: 99%

“…However, these frameworks assume that resource demand is known before applications' runtime and is not fluctuated which may not be true for most cases. From this reason, we have designed a framework called a Robust Energy-Efficient framework which was proposed in [4].…”

Section: Introductionmentioning

confidence: 99%

“…The work in [4] explores how to dynamically generate placement scheme for all processes in the system. Application processes initially run on any available machine.…”

Section: Introductionmentioning

confidence: 99%

“…Optimization is also performed in order to generate a good process relocation plan. This paper presents a dynamic scheduling paradigm, called the Placement Scheme Generator (PSG) to be used within the framework presented in [4]. The main objective of PSG is to keep a data center in its energy-efficient state most of the time.…”

Section: Introductionmentioning

confidence: 99%

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Process placement scheme optimization for energy-efficient data center

Tiwari

Jintamuttha

Manakul

et al. 2012

2012 9th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolog

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The energy cost of a typical data center is usually much higher than those standard office buildings. Inefficiency in energy management can thus hurt a company. Currently, there are many commercial software that emphasize how to measure and control the energy usage. However, most of these available packages are not able to accurately predict behaviors of various applications submitted to a data center resulting in difficulties in energy-efficient optimization. A robust energy-efficient framework is then proposed. The framework allows a process to migrate among machines during execution. This paper presents an algorithm related to a process placement scheme generation employed in such a framework. The algorithm is a heuristic method designed based on Artificial Bee Colony and Paretodomination. A simulation-based experiment is designed to study our method efficiency during live migration. The results suggested that our generated placement scheme provides 21-38% averaged improvement when compared with traditional scheduling algorithms used in data centers.

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“…In this paper, we extend the work in [4] to design the PSG module. The main task of PSG is to determine a set of suitable computers for each process in a data center.…”

Section: Energy-efficiency-based Placement Scheme Generationmentioning

confidence: 98%

“…The general idea is described in Fig.1. PSG requires process and machine profiles [4]. Process profile describes the resource usage behavior of each process during a time slot, T SLOT .…”

Section: Energy-efficiency-based Placement Scheme Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The work in [4] explores how to dynamically generate placement scheme for all processes in the system. Application processes initially run on any available machine.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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