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Algorithms for Energy Efficient Load Balancing in Cloud Environments

Title: Algorithms for Energy Efficient Load Balancing in Cloud Environments

Seminar Paper , 2013 , 17 Pages , Grade: 1.0

Autor:in: Norman Peitek (Author)

Computer Science - Commercial Information Technology
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Summary Excerpt Details

Energy efficiency has a rising importance throughout society. With the growth of large data centers, the energy consumption becomes centralized and nowadays takes a significant amount of the overall electricity consumption of a country. Load balancing algorithms are able to make an existing infrastructure more efficient without major drawbacks. This structured literature research presents the state of the art technology regarding the load balancing approach to make data centers more en-ergy efficient. The state of the art approaches are reviewed for techniques, im-provements and consideration of performance effects.

Excerpt


Inhaltsverzeichnis (Table of Contents)

  • Introduction
  • Load Balancing in Cloud Environments
  • Search Strategy and Review Protocol
    • Research Goals
    • Search Term

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This structured literature review aims to examine the state-of-the-art technology regarding load balancing algorithms for energy efficiency in data centers. The study investigates existing approaches, analyzes techniques and improvements, and considers the potential performance effects of these algorithms.

  • Energy efficiency in cloud computing
  • Load balancing algorithms for data centers
  • Techniques for energy reduction in cloud environments
  • Performance impacts of energy-efficient load balancing
  • Measurement methods for energy efficiency improvements

Zusammenfassung der Kapitel (Chapter Summaries)

The introduction highlights the increasing importance of energy efficiency in modern society, particularly with the rise of cloud computing and large data centers. The growing energy demand of data centers, which can account for a significant portion of a country's electricity consumption, necessitates a focus on energy efficiency. Load balancing algorithms are presented as a potential solution to optimize existing infrastructure and reduce energy consumption without significant drawbacks.

Chapter 2 delves into the concept of load balancing in cloud environments, emphasizing how it can contribute to energy savings. It explores three key techniques for energy efficiency: overallocation, live migration, and server shutdown. The chapter explains the mechanisms behind these techniques, considering potential challenges and considerations.

Chapter 3 outlines the research strategy and protocol used in this literature review. It specifies the research goals, aiming to answer questions about techniques used for energy efficiency improvement, measurement methods for these improvements, and potential performance impacts of load balancing algorithms. The chapter details the search terms used to gather relevant literature and the criteria for selecting and refining the research pool.

Schlüsselwörter (Keywords)

The primary focus of this paper is on energy efficiency in cloud computing environments, particularly through the application of load balancing algorithms. The study investigates techniques such as overallocation, live migration, and server shutdown, as well as their potential impact on performance. The keywords encapsulate the core themes and concepts of the paper, namely energy efficiency, load balancing, and cloud computing.

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Details

Title
Algorithms for Energy Efficient Load Balancing in Cloud Environments
College
Otto-von-Guericke-University Magdeburg  (Faculty of Computer Science)
Course
Recent Topics in Business Informatics
Grade
1.0
Author
Norman Peitek (Author)
Publication Year
2013
Pages
17
Catalog Number
V286584
ISBN (eBook)
9783656868705
ISBN (Book)
9783656868712
Language
English
Tags
Load Balancing Cloud Computing Data Center
Product Safety
GRIN Publishing GmbH
Quote paper
Norman Peitek (Author), 2013, Algorithms for Energy Efficient Load Balancing in Cloud Environments, Munich, GRIN Verlag, https://www.grin.com/document/286584
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