Abstract
This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large-scale disruption. We give a formulation of the problem as a mixed integer linear programming and show that it is NP-hard. We propose a polynomial time heuristic, called iterative split and prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. ISP's decisions are guided by the use of a new notion of demand-based centrality of nodes. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared with several greedy approaches, ISP performs better in terms of total cost of repaired components and does not result in any demand loss. It performs very close to the optimal when the demand is low with respect to the supply network capacities, thanks to the ability of the algorithm to maximize sharing of repaired resources.
Recommended Citation
N. Bartolini et al., "On Critical Service Recovery after Massive Network Failures," IEEE/ACM Transactions on Networking, vol. 25, no. 4, pp. 2235 - 2249, article no. 7896641, Institute of Electrical and Electronics Engineers, Aug 2017.
The definitive version is available at https://doi.org/10.1109/TNET.2017.2688330
Department(s)
Computer Science
Keywords and Phrases
flow restoration; massive network disruption; Network recovery
International Standard Serial Number (ISSN)
1063-6692
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Aug 2017
