DocumentCode
1379461
Title
Distributed adaptive diverse routing for voice-over-IP in service overlay networks
Author
Li, Hong ; Mason, Lorne ; Rabbat, Michael
Author_Institution
Electr. & Comput. Eng. Dept., McGill Univ., Montreal, QC, Canada
Volume
6
Issue
3
fYear
2009
fDate
9/1/2009 12:00:00 AM
Firstpage
175
Lastpage
189
Abstract
This paper proposes a novel mechanism to discover delay-optimal diverse paths using distributed learning automata for Voice-over-IP (VoIP) routing in service overlay networks. In addition, a novel link failure detection method is proposed for detecting and recovering from link failures to reduce the number of dropped voice sessions. The main contributions of this paper are a decentralized, scalable method for minimizing delay on both a primary and secondary path between all pairs of overlay nodes, while at the same time maintaining the link disjointness between the primary and the secondary optimal paths. Simulations of a 50-node model of AT&T´s backbone network show that the proposed method improves the quality of voice calls from unsatisfactory to satisfactory, as measured by the R-factor. With the proposed link failure detection mechanism, the time to recover from a link failure is considerably reduced.
Keywords
Internet telephony; adaptive systems; failure analysis; telecommunication links; telecommunication network routing; R-factor measurement; delay optimal diverse paths; distributed adaptive diverse routing; distributed learning automata; dropped voice sessions reduction; link failure detection method; link failures recovery; primary secondary optimal path; service overlay networks; voice-over-IP; Delay; IP networks; Internet telephony; Learning automata; Quality of service; Routing; Search methods; Telecommunication traffic; Traffic control; Web and internet services; Diverse routing, reinforcement learning, voice-over-IP, overlay networks.;
fLanguage
English
Journal_Title
Network and Service Management, IEEE Transactions on
Publisher
ieee
ISSN
1932-4537
Type
jour
DOI
10.1109/TNSM.2009.03.090304
Filename
5374838
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