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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/1823
Title: Dynamic overload control for distributed call processors using the neural network method
Authors: Wu, Si
Wong, Michael Kwok-Yee
Keywords: Dynamic overload control
Distributed call processors
Network method
Call processing computers
Traffic peaks
Issue Date: 1998
Citation: IEEE transactions on neural networks, v. 9, no. 6, Nov. 1998, p. 1377-1387
Abstract: Overload control of call processors in telecom networks is used to protect the network of call processing computers from excessive load during traffic peaks, and involves techniques of predictive control with limited local information. Here we propose a neural network algorithm, in which a group of neural controllers are trained using examples generated by a globally optimal control method. Simulations show that the neural controllers have better performance than local control algorithms in both the throughput and the response to traffic upsurges. Compared with the centralized control algorithm, the neural control significantly decreases the computational time for making decisions and can be implemented in real time.
Rights: © 1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
URI: http://hdl.handle.net/1783.1/1823
Appears in Collections:PHYS Journal/Magazine Articles
CSE Journal/Magazine Articles

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