A novel approach for failure localization in all-optical mesh networks

Authors:
János Tapolcai;Bin Wu;Pin-Han Ho;Lajos Rónyai
Affiliations:
Department of Telecommunications and Media Informatics, Budapest University of Technology, Budapest, Hungary;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Computer and Automation Research Institute, Hungarian Academy of Sciences, Budapest, Hungary and Institute of Mathematics, Budapest University of Technology, Budapest, Hungary
Venue:
IEEE/ACM Transactions on Networking (TON)
Year:
2011

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Abstract

Achieving fast and precise failure localization has long been a highly desired feature in all-optical mesh networks. Monitoring trail (m-trail) has been proposed as the most general monitoring structure for achieving unambiguous failure localization (UFL) of any single link failure while effectively reducing the amount of alarm signals flooding the networks. However, it is critical to come up with a fast and intelligent m-trail design approach for minimizing the number of m-trails and the total bandwidth consumed, which ubiquitously determines the length of the alarm code and bandwidth overhead for the m-trail deployment, respectively. In this paper, the m-trail design problem is investigated. To gain a deeper understanding of the problem, we first conduct a bound analysis on the minimum length of alarm code of each link required for UFL on the most sparse (i.e., ring) and dense (i.e., fully meshed) topologies. Then, a novel algorithm based on random code assignment (RCA) and random code swapping (RCS) is developed for solving the m-trail design problem. The algorithm is verified by comparison to an integer linear program (ILP) approach, and the results demonstrate its superiority in minimizing the fault management cost and bandwidth consumption while achieving significant reduction in computation time. To investigate the impact of topology diversity, extensive simulation is conducted on thousands of random network topologies with systematically increased network density.