Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/36944
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Conference paper |
Title: | Multicast-based inference of network-internal loss performance |
Author: | Tian, H. Shen, H. |
Citation: | Proceedings of the 7th International Symposium on Parallel Architectures, Algorithms and Networks, (ISPAN 2004), pp. 288-293 |
Publisher: | IEEE |
Publisher Place: | Online |
Issue Date: | 2004 |
ISBN: | 0769521355 |
Conference Name: | International Symposium on Parallel Architectures, Algorithms and Networks (7th : 2004 : Hong Kong) |
Statement of Responsibility: | Hui Tian, Hong Shen |
Abstract: | The use of multicast traffic as measurement probes is efficient and effective to infer network-internal characteristics. We propose a new statistical approach to infer network internal link loss performance from end-to-end measurements. Incorporating with the procedure of topology inference, we present an inference algorithm that can infer loss rates of individual links in the network when it infers the network topology. It is proved that the loss rate inferred by our approach is consistent with the real loss rate as the number of probe packets tends to infinity. The approach is also extended to general trees case for loss performance inference. Loss rate-based scheme on topology inference is built in view of correct convergence to the true topology for general trees. |
Description: | ©2004 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. |
DOI: | 10.1109/ISPAN.2004.1300494 |
Published version: | http://dx.doi.org/10.1109/ispan.2004.1300494 |
Appears in Collections: | Aurora harvest Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_36944.pdf | 127.6 kB | Publisher's PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.