TY - GEN
T1 - Network recovery after massive failures
AU - Bartolini, Novella
AU - Ciavarella, Stefano
AU - Porta, Thomas F.La
AU - Silvestri, Simone
N1 - Funding Information:
This work was supported by the Defense Threat Reduction Agency under the grant HDTRA1-10-1-0085. The work of Novella Bartolini was sponsored by the U.S. Army Research Laboratory under Agreement Number W911NF-14-0610.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/29
Y1 - 2016/9/29
N2 - This paper addresses the problem of efficientlyrestoring sufficient resources in a communications network tosupport the demand of mission critical services after a large scaledisruption. We give a formulation of the problem as an MILPand show that it is NP-hard. We propose a polynomial timeheuristic, called Iterative Split and Prune (ISP) that decomposesthe original problem recursively into smaller problems, untilit determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and thedisruption model. Compared to several greedy approaches ISPperforms better in terms of number of repaired components, and does not result in any demand loss. It performs very close tothe optimal when the demand is low with respect to the supplynetwork capacities, thanks to the ability of the algorithm tomaximize sharing of repaired resources.
AB - This paper addresses the problem of efficientlyrestoring sufficient resources in a communications network tosupport the demand of mission critical services after a large scaledisruption. We give a formulation of the problem as an MILPand show that it is NP-hard. We propose a polynomial timeheuristic, called Iterative Split and Prune (ISP) that decomposesthe original problem recursively into smaller problems, untilit determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and thedisruption model. Compared to several greedy approaches ISPperforms better in terms of number of repaired components, and does not result in any demand loss. It performs very close tothe optimal when the demand is low with respect to the supplynetwork capacities, thanks to the ability of the algorithm tomaximize sharing of repaired resources.
UR - http://www.scopus.com/inward/record.url?scp=84994311385&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84994311385&partnerID=8YFLogxK
U2 - 10.1109/DSN.2016.18
DO - 10.1109/DSN.2016.18
M3 - Conference contribution
AN - SCOPUS:84994311385
T3 - Proceedings - 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
SP - 97
EP - 108
BT - Proceedings - 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 46th IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2016
Y2 - 28 June 2016 through 1 July 2016
ER -