Paper Info
Title
SRLG failure localization using nested m‐trails and their application to adaptive probing
Abstract
This article explores a recently introduced novel technique called the nested monitoring trail (m-trail) method in all-optical mesh networks for failure localization of any shared risk link group (SRLG) with up to d undirected links. The nested m-trail method decomposes each network topology that is at least d-connected into virtual cycles and trails, in which sets of m-trails that traverse through a common monitoring node (MN) can be obtained. The nested m-trails are used in the monitoring burst (m-burst) framework, in which the MN can localize any SRLG failure by inspecting the optical bursts traversing through it. An integer linear program (ILP) and a heuristic are proposed for the network decomposition, which are further verified by numerical experiments. We show that the proposed method significantly reduces the required fault localization latency compared with the existing methods. Finally, we demonstrate that nested mtrails can also be used in adaptive probing to find SRLG faults in all-optical networks. The nested m-trail based probing method needs a significantly reduced number of sequential probes. Thus, the method overcomes one of the important hurdles to deploy adaptive probing in alloptical networks: the large number of sequential probes needed to localize SRLG faults. (c) 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 347-363 2015
Year
DOI
Venue
2015
10.1002/net.21653
NETWORKS
Keywords
Field
DocType
shared risk link group,dual-link,multilink,monitoring trail,unambiguous failure localization,wavelength links,monitoring delay,fault localization latency,disjoint paths,adaptive probing
Integer,Mesh networking,Heuristic,Latency (engineering),Network topology,Linear programming,Shared risk link group,Mathematics,Traverse,Distributed computing
Journal
Volume
Issue
ISSN
66.0
SP4.0
0028-3045
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Mohammed L. Ali182.40
Pin-Han Ho23020233.38
János Tapolcai336441.42