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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/742

Title: Modeling the telephone call network
Authors: Tam, Wai M.
Lau, Francis Chung-ming
Tse, C. K. Michael
Subjects: Large scale systems
Real time systems
Telephone network
Telephone numbers
Issue Date: 2007
Publisher: IEEE
Citation: ISCAS 2007 : 2007 IEEE International Symposium on Circuits and Systems : New Orleans, Louisiana, May 27-30, 2007, proceedings, p. 453-456.
Abstract: It is natural to envisage that in a telephone network, some telephone numbers originate or receive more calls than others. Indeed, real-life data have verified the conjecture that the number of calls originated from or received by a telephone number in a network has a power-law property. Further, the number of calls made or received by the same telephone number can be very different. In this paper, we construct a self-growing complex network for modeling the aforementioned telephone call network. The complex network obtained is a directed and weighted network. Moreover, the nodes (telephone numbers) of the network exhibit power-law properties in the following aspects: total-degree, out-degree, in-degree, total-strength, out-strength and in-strength.
Rights: © 2007 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 holders.
Type: Conference Paper
URI: http://hdl.handle.net/10397/742
ISBN: 1424409217
Appears in Collections:EIE Conference Papers & Presentations

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