Author :
Heydarikiya, Fatemeh ; Toroghy Haghighat, Abolfazl ; Heydarikiya, Maryam
Author_Institution :
Software Eng., Ghazvin Azad Univ., Qazvin, Iran
Abstract :
Notice of Violation of IEEE Publication Principles
"e-STAB: Energy-efficient Scheduling for Cloud Computing Applications with Traffic Load Balancing,"
by Fatemeh Heydarikiya, Abolfazl Toroghy Haghighat, Maryam Heydarikiya
in the 2014 8th International Conference on e-Commerce in Developing Countries: With Focus on e-Trust (ECDC), April 2014
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE???s Publication Principles.
This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"e-STAB: Energy-Efficient Scheduling for Cloud Computing Applications with Traffic Load Balancing,"
by Dzmitry Kliazovich, Sisay T Arzo, Fabrizio Granelli, Pascal Bouvry, Samee Ullah Khan
in the IEEE International Conference on and IEEE Cyber, Physical and Social Computing Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), August 2013
Energy consumption accounts for a large percentage of the operational expenses in data centers that are used as backend computing infrastructure for cloud computing. Existing solutions for energy efficiency and job scheduling are focusing on job distribution between servers based on the computational demands, while the communication demands are ignored. This work emphases the role of communication fabric and presents a scheduling solution, named e-STAB, which takes into account traffic requirements of cloud applications providing energy efficient job allocation and traffic load balancing in data center- networks. Effective distribution of network traffic improves quality of service of running cloud applications by reducing the communication-related delays and congestion-related packet losses. The validation results, obtained from the GreenCloud simulator, underline benefits and efficiency of the proposed scheduling methodology.
Keywords :
cloud computing; computer centres; power aware computing; quality of service; resource allocation; scheduling; GreenCloud simulator; backend computing infrastructure; cloud computing applications; communication demands; communication fabric; communication-related delay reduction; computational demands; congestion-related packet loss reduction; data center networks; data centers; e-STAB; energy consumption; energy efficient job allocation; energy-efficient scheduling; job distribution; job scheduling; network traffic distribution; operational expenses; quality of service; traffic load balancing; traffic requirements; Current measurement; Energy measurement; Green products; Load management; Power measurement; Servers; Switches; cloud computing; data centers; energy-efficient scheduling; load balancing;
