Good Solution for Resource Distribution: Multi-Agent & Cloud Computing in Distributed Data Mining

(*) Corresponding author

Authors' affiliations

DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)


Get valid details from big databases concerning petabytes has an unusual usefulness. Nonetheless, to startup a data mining system, it involves excessive work and takes a lot of time for a positive achievement in some distributed environments. Also, cloud computing came to existence and proves to be the future of modern day computing and the appropriate solution for resource distribution. We suggest an agent based system working under a cloud service (SaaS) architecture as a perfect DDM system.
Copyright © 2017 Praise Worthy Prize - All rights reserved.


Distributed Data Mining; Cloud Computing; Multi-Agent Systems

Full Text:



Aljabr, M., Using Data Mining Techniques in Building Dataset for Network Intrusion Detection, (2015) International Review on Computers and Software (IRECOS), 10 (7), pp. 652-659.

Asha, P., Jebarajan, T., Improved Parallel Pattern Growth Data Mining Algorithm, (2014) International Review on Computers and Software (IRECOS), 9 (1), pp. 80-87.

D. Sharma, F. Shadabi, Multi-Agents Based Data Mining for Intelligent Decision Support Systems , 2014 2nd International Conference on Systems and Informatics 978-1-4799-5458-2 ©2014 IEEE (ICSAI 2014).

A. Fariz, J. Abouchabaka, N. Rafalia, Using Multi-Agents Systems In Distributed Datamining: A Survey. Journal of Theoretical and Applied Information Technology Vol.73 No.3 427-441 (JATIT 2015).

D. Chekired, L. Khoukhi, Smart Grid Solution for Charging and Discharging Services Based on Cloud Computing Scheduling, IEEE Transactions on Industrial Informatics ( Volume: 13, Issue: 6, Dec. 2017 ), Page(s): 3312 - 3321.

Cisco Global Cloud Index: Forecast and Methodology,2010-2015

J.O. Gutierrez-Garcia and K.M. Sim, “A Family of Heuristics for Agent-based Elastic Cloud Bag-of-Tasks Concurrent Scheduling,” Future Generation Computer Systems, Volume 29, Issue 7, September 2013, Pages 1682-1699.

J. O. Gutierrez-Garcia and K. M. Sim, “GA-based Cloud Resource Estimation for Agent-based Execution of Bag-of-tasks Applications,” Information Systems Frontiers, (September 2011).

J. Ejarque, R. Sirvent , R. M. Badia. A Multi-agent approach for Semantic Resource Allocation. Cloud Computing Technology and Science (CloudCom), 2010 IEEE Second International Conference: Pages 335 – 342.

M. Kim, H. Lee, W. Nam. A Model of multi-agent design for virtualization resource configuration in Cloud Computing. Computers, Networks, Systems and Industrial Engineering (CNSI), 2011 First ACIS/JNU International Conference: Pages 234 – 239.

M. Kim, H. Lee, H. Yoon, J. Kim, H. Kim, IMAV: An Intelligent Multi-Agent Model Based on Cloud Computing for Resource Virtualization, ICIEE 2011, May 28-29, IPCSIT Vol.6, pp. 199-203, ISBN 978-981-08-8637-0.

M. Paletta, P. Herrero. A MAS based Negotiation Mechanism to deal with Service Collaboration in Cloud Computing. Intelligent Networking and Collaborative Systems, 2009. INCOS '09. International Conference: Pages 147 – 153.

Neto, D.O.G., Jr., W.M., Ferreira, R.: Anteater: A Service-Oriented Architecture for High-Performance Data Mining. IEEE Internet Computing (2006) 36-43.

V. Gorodetsky, O. Karsaeyv, V. Samoilov. Software Tool For Agent-Based Distributed Data Mining. Conference on Computational Intelligence and Multimedia Applications 2007 International Conference on (2007) Vol2, Publisher: IEEE, Pages: 18-24.

F. Gandon, R. Dieng-Kuntz, O. Corby, A. Giboin. Web Sémantique et Approche Multi-Agents pour la Gestion d'une Mémoire Organisationnelle Distribuée. INRIA - Projet ACACIA, 2004, route des Lucioles, B.P. 93, 06902 Sophia Antipolis, France.


Please send any question about this web site to
Copyright © 2005-2024 Praise Worthy Prize