An Efficient Method to Reduce Energy Consumption in Cloud Computing using Multi-Agent Systems

Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
View: 549

This Paper With 9 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

NPECE01_069

تاریخ نمایه سازی: 6 بهمن 1395

Abstract:

Cloud Computing is an emerging concept combining many fields of computing. It provides services,software and processing capacity over the internet. Cloud computing is abundantly accepted by the business markets and organizations. Data centers host hundreds or thousands of servers comprised of software and hardware to respond to the clients' requests. A large amount of energy is consumed by data centers to provide promised services. The power consumption in data centers raises many serious issues including excessive carbon dioxide emission; therefore, many solutions have been offered and much research has been done to reduce energy consumption in data centers. Task scheduling has effect on energy consumed by datacenters. One of the important factors for task scheduling is how the tasks can access their required data. Certainly, delay in accessing data by tasks can impress on the total completiontime. This paper presents a multi- agent system which is used for task scheduling in cloud to reduce the energy consumption of data centers.

Authors

Elham Khodabakhsh

Student of Department of Computer Engineering, Islamic Azad University, UAE Branch, Dubai, UAE,

Hamid Reza Naji

Associate Professor of Department of Computer Engineering, Islamic Azad University, UAE Branch, Dubai, UAE

Mohammad Malakoti

Associate Professor of Department of Computer Engineering, Islamic Azad University, UAE Branch,Dubai, UAE,

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
  • []piao, Jing Tai, and Jun Yan. "A network-aware virtual machine ...
  • Dong, Yu-Shuang, Gao-Chao Xu, and Xiao-Dong Fu. "A distributed parallel ...
  • [] Srivastava, Shivangi, Parvez Mahmood Kha, and Rizwan Beg "Energy ...
  • [" jresfatsion, S. K., E. Wadbro, and J. Tordsso. "A ...
  • [] Mishra, Rina, Sonali Jain, and Nirupama Kurmi. "An Emerging ...
  • [] M. Steinder , D. Carrera, I. Whalley, J. Torres ...
  • Ning Liu, Ziqian Dong, Roberto Rojas-Cessa, _ Task and Server ...
  • Tesfatsion, S. K., Eddie Wadbro, and Johan Tordsson. "A com ...
  • http://www. da ta cen terknowledge. com/arch ives/2011/12/14/h ow-manydata- cen ters-em ...
  • "Google ses over one million servers" Accessed: September ...
  • نمایش کامل مراجع