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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 83 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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A Brief Review on the Validity and Reliability of Microsoft Kinect Sensors for Functional Assessment Applications, DIAZ-MONTERROSAS, P. R., POSADA-GOMEZ, R., MARTINEZ-SIBAJA, A., AGUILAR-LASSERRE, A. A., JUAREZ-MARTINEZ, U., TRUJILLO-CABALLERO, J. C.
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Cascaded Feature Selection for Enhancing the Performance of Collaborative Recommender System, AL-SHAMRI, M. Y. H., AL-JUNIAD, A. F., QAID, T. S., AHMED, M. H. A., RAWEH, A. A.
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Analysis of Channel Transfer Functions in Power Line Communication System for Smart Metering and Home Area Network, MLYNEK, P., HASIRCI, Z., MISUREC, J., FUJDIAK, R.
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All-Weather Road Image Enhancement using Multicolor Content-Aware Color Constancy, LEE, D., KIM, T., BYUN, H., CHOI, Y.
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Experimental Method of Determining the Equivalent Circuit Parameters of a Switched Reluctance Machine, VUKADINOVIC, D., GRBIN, S., BASIC, M.
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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  3/2009 - 5

A New Randomized Algorithm for Handling Scheduling Conflicts in Grids

VAHDAT-NEJAD, H. See more information about VAHDAT-NEJAD, H. on SCOPUS See more information about VAHDAT-NEJAD, H. on IEEExplore See more information about VAHDAT-NEJAD, H. on Web of Science, ZAMANIFAR, K. See more information about ZAMANIFAR, K. on SCOPUS See more information about ZAMANIFAR, K. on SCOPUS See more information about ZAMANIFAR, K. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (417 KB) | Citation | Downloads: 912 | Views: 3,757

Author keywords
coordination, distributed system, grid, randomized algorithms, scheduling

References keywords
scheduling(6), distributed(6), computing(5), grid(4), algorithm(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2009-10-26
Volume 9, Issue 3, Year 2009, On page(s): 22 - 26
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2009.03005
Web of Science Accession Number: 000271872000005
SCOPUS ID: 77954634405

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As the scale of Grid platforms grows, the idea of a centralized scheduler loses its efficiency, and it is replaced with the scheme of decentralized schedulers. However, a new problem emerges in distributed scheduling systems, which is how to coordinate the autonomous schedulers to avoid the occurrence of conflicting schedules. In this paper, by exploiting the idea of randomized algorithms, a new scheduling scheme has been proposed, which addresses the problem of scheduling conflicts. The proposed algorithm is thoroughly decentralized in the sense that there is no central point of contact in the system. In addition, our approach is a suitable way toward reaching scalability and autonomy in future Grids. We prove the feasibility and effectiveness of the proposed algorithm through statistical analysis.

References | Cited By  «-- Click to see who has cited this paper

[1] I. Foster and C. Kesselman, grid: "Blueprint for a new computing infrastructure", Morgan Kaufmann Publishers, USA, 1998 [PermaLink]

[2] Hamed Vahdat-Nejad, Reza Monsefi, Hossein Deldari, "Distributed resource scheduling in grid computing using fuzzy approach", Proceedings of the International Conference on Information and Knowledge Technology, Iran, 2007

[3] HU Rong, HU Zhigang, "A scheduling algorithm aimed at time and cost for meta-tasks in grid computing using fuzzy applicability", Proceedings of the eighth International Conference on High-performance Computing in Asia-pacific region, IEEE 2005
[CrossRef] [Web of Science Record] [SCOPUS Times Cited 6]

[4] Hamed Vahdat-Nejad, Reza Monsefi, Mahmoud Naghibzadeh, "A new fuzzy algorithm for global job scheduling in multiclusters and grids", Proceedings of International Conference on Computational Intelligence for Measurement Systems and Applications, Italy, 2007
[CrossRef] [Web of Science Record] [SCOPUS Times Cited 3]

[5] Hamed Vahdat-Nejad, Reza Monsefi, "Static parallel job scheduling in computational grids", Proceedings of the International Conference on Computer and Electrical Engineering, Thailand, 2008
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 5]

[6] Rajiv Ranjan, Aaron Harwood, Rajkumar Buyya, "A case for cooperative and incentive-based federation of distributed clusters", Future generation computer systems, Elsevier, 2007
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 22]

[7] Ashraf Osman, "Introduction to randomized algorithms", West Virginia University

[8] Rajiv Ranjan, Mustafizur Rahman, and Rajkumar Buyya, "A decentralized and cooperative workflow scheduling algorithm", Proceedings of eighth IEEE International Symposium on Cluster Computing and the Grid, 2008
[CrossRef] [SCOPUS Times Cited 26]

[9] Hoong Chuin Lau, Shih Fen Cheng, Thin Yin Leong, "Multi-period combinatorial auction mechanism for distributed resource allocation and scheduling", Proceedings of IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2007
[CrossRef] [SCOPUS Times Cited 16]

[10] Olivier Beaumont, Larry Carter, Jeanne Ferrante, Arnaud Legrand, Loris Marchal, and Yves Robert, "Centralized versus distributed schedulers for bag-of-tasks applications", IEEE Transactions on Parallel and Distributed Systems, Volume 19, No 5, May 2008
[CrossRef] [Web of Science Times Cited 25] [SCOPUS Times Cited 39]

[11] L. Walras, "Elements of pure economics", Allen and Unwin, English translation by William Jaffe 1954 (originally published in 1874) [PermaLink]

[12] J. Q. Cheng and M. P. Wellmam, "The WALAS algorithm: A convergent distributed implementation or general equilibrium outcomes", Computational Econ. 12: 1-24, 1998

References Weight

Web of Science® Citations for all references: 42 TCR
SCOPUS® Citations for all references: 117 TCR

Web of Science® Average Citations per reference: 3 ACR
SCOPUS® Average Citations per reference: 9 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-02-16 00:57 in 51 seconds.

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Faculty of Electrical Engineering and Computer Science
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