DocumentCode
460805
Title
Notice of Violation of IEEE Publication Principles
A New Predictive Mechanism Based on Artificial Neural Network
Author
Dong Li ; Wenqiang Yu
Author_Institution
Sch. of Eng. & Technol., Shandong Univ. of Technol.
Volume
1
fYear
2006
fDate
3-6 Nov. 2006
Firstpage
333
Lastpage
338
Abstract
Notice of Violation of IEEE Publication Principles
"A New Predictive Mechanism Based on Artificial Neural Network,"
by Dong Li and Wenqiang Yu,
in the Proceedings of the International Conference on Computational Intelligence and Security, Nov. 2006 pp. 333-338
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 near verbatim copy of the papers cited below. The original text was copied without attribution.
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:
"A Neural Network Based Predictive Mechanism for Available Bandwidth,"
by Alaknantha Eswaradass, Xian-He Sun and Ming Wu,
in the Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, April 2005
Many recent developments of computer technology, such as Web services, Grid, peer-to-peer, and mobile computing, are network-based computing. Their applicability depends on the availability of the underlying network bandwidth. However, network resources are shared and the available network bandwidth varies with time. There is no satisfactory solution available for network performance predictions. This lack of prediction limits the applicability of network-based computing, especially for grid computing where concurrent remote processing is essential. In this paper, we propose an artificial neural network (ANN) based approach for network performance prediction. The ANN mechanism has been tested on classical trace files and compared with the well-known system NWS (Network Weather Service) for performance. Experimental results show the ANN approach always provides an improved prediction over that of NWS
"A New Predictive Mechanism Based on Artificial Neural Network,"
by Dong Li and Wenqiang Yu,
in the Proceedings of the International Conference on Computational Intelligence and Security, Nov. 2006 pp. 333-338
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 near verbatim copy of the papers cited below. The original text was copied without attribution.
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:
"A Neural Network Based Predictive Mechanism for Available Bandwidth,"
by Alaknantha Eswaradass, Xian-He Sun and Ming Wu,
in the Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, April 2005
Many recent developments of computer technology, such as Web services, Grid, peer-to-peer, and mobile computing, are network-based computing. Their applicability depends on the availability of the underlying network bandwidth. However, network resources are shared and the available network bandwidth varies with time. There is no satisfactory solution available for network performance predictions. This lack of prediction limits the applicability of network-based computing, especially for grid computing where concurrent remote processing is essential. In this paper, we propose an artificial neural network (ANN) based approach for network performance prediction. The ANN mechanism has been tested on classical trace files and compared with the well-known system NWS (Network Weather Service) for performance. Experimental results show the ANN approach always provides an improved prediction over that of NWS
Keywords
Web services; grid computing; mobile computing; neural nets; peer-to-peer computing; performance evaluation; Network Weather Service; Web services; artificial neural network; computer technology; grid computing; mobile computing; network bandwidth; network performance predictions; network resources; network-based computing; peer-to-peer; predictive mechanism; remote processing; Artificial neural networks; Bandwidth; Computational intelligence; Computer networks; Concurrent computing; Distributed computing; Grid computing; Notice of Violation; Peer to peer computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security, 2006 International Conference on
Conference_Location
Guangzhou
Print_ISBN
1-4244-0604-8
Type
conf
DOI
10.1109/ICCIAS.2006.294150
Filename
4072103
Link To Document