Abstract
A number of models have been proposed to analyze interdependent networks in recent years. However most of the models are unable to capture the complex interdependencies between such networks. To overcome the limitations, we have recently proposed a new model. Utilizing this model, we provide techniques for progressive recovery from failure. The goal of the progressive recovery problem is to maximize the system utility over the entire duration of the recovery process. We show that the problem can be solved in polynomial time in some special cases, whereas for some others, the problem is NP-complete. We provide two approximation algorithms with performance bounds of 2 and 4 respectively. We provide an optimal solution utilizing Integer Linear Programming and a heuristic. We evaluate the efficacy of our heuristic with both synthetic and real data collected from Phoenix metropolitan area. The experiments show that our heuristic almost always produces near optimal solution.
This research is supported in part by a grant from the U.S. Defense Threat Reduction Agency under grant number HDTRA1-09-1-0032 and by a grant from the U.S. Air Force Office of Scientific Research under grant number FA9550-09-1-0120.
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Mazumder, A., Zhou, C., Das, A., Sen, A. (2016). Progressive Recovery from Failure in Multi-layered Interdependent Network Using a New Model of Interdependency. In: Panayiotou, C., Ellinas, G., Kyriakides, E., Polycarpou, M. (eds) Critical Information Infrastructures Security. CRITIS 2014. Lecture Notes in Computer Science(), vol 8985. Springer, Cham. https://doi.org/10.1007/978-3-319-31664-2_38
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DOI: https://doi.org/10.1007/978-3-319-31664-2_38
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