Abstract

Delay tomography is an inference technique for link delays in a network, where end-to-end route measurement is a promising method to reduce measurement overhead. Furthermore, by incorporating compressed sensing, delay tomography can efficiently detect sparse anomaly. In delay tomography, however, there is an inevitable issue that is clock synchronization for the route measurements. In this paper, based on route referencing, we study synchronization-free delay tomography with compressed sensing. From theoretical analysis, optimal route referencing and ordering methods for synchronization-free delay tomography are derived as “subtractive and differential schemes,” which cancel or minimize the error factors caused by clock asynchronism, clock skew, and normal link delays with single or multiple references, respectively. Simulation experiments confirm that the proposed methods can identify abnormal links more accurately with robustness against the error factors than a conventional scheme, where the newly proposed differential scheme always shows the best performance thanks to its better error factors cancelation.

Details

Title
Route referencing and ordering for synchronization-free delay tomography in wireless networks
Author
Nakanishi, Kensuke 1 ; Naka, Teruhito 2 ; Hara, Shinsuke 2 ; Matsuda, Takahiro 3 ; Takizawa, Kenichi 4 ; Ono, Fumie 4 ; Miura, Ryu 4 

 Wireless System Laboratory, Corporate Research & Development Center, Toshiba Corp., Kanagawa, Japan 
 Graduate School of Engineering, Osaka City University, Osaka, Japan 
 Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan 
 National Institute of Information and Communications Technology (NICT), Kanagawa, Japan 
Pages
1-15
Publication year
2018
Publication date
Aug 2018
Publisher
Springer Nature B.V.
ISSN
16871472
e-ISSN
16871499
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2092379056
Copyright
EURASIP Journal on Wireless Communications and Networking is a copyright of Springer, (2018). All Rights Reserved., © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.