NDLI: A proactive risk-aware robotic sensor network for Critical Infrastructure Protection

Content Provider	IEEE Xplore Digital Library
Author	McCausland, J. Di Nardo, G. Falcon, R. Abielmona, R. Groza, V. Petriu, E.
Copyright Year	2013
Description	Author affiliation: Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada (McCausland, J.; Falcon, R.; Abielmona, R.; Groza, V.; Petriu, E.) \|\| Res. & Eng., Larus Technol. Corp., Ottawa, ON, Canada (Di Nardo, G.)
Abstract	In this paper, a risk-aware robotic sensor network (RSN) is proposed in the context of Critical Infrastructure Protection. Such a network will be comprised of mobile sensor nodes that perceive various aspects of their environment and topologically reconfigure in order to secure a strategic area of interest. Risk awareness is provided through the application of a recently developed Risk Management Framework to the RSN. The risk level of each node is assessed in terms of their degree of distress, proximity factor, and terrain maneuverability. Risk monitoring alerts are issued whenever any given sensor node's quantitative risk metric exceeds a user-defined threshold value. At this point, a node-in-distress (NID) has been identified as the weak point of the securing structure around which the RSN is deployed. The NID can no longer be used with confidence and the effective perimeter coverage of the RSN has been reduced, thus creating potential security breaches in the area of interest. In response, the remaining nodes will self-organize to maximize the perimeter coverage while minimizing the cost of doing so. A limited set of contingency network topologies is produced via evolutionary multi-objective optimization using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) and then ranked according to a human-guided alternative selection algorithm. The security operator picks the most suitable topology, which is then effectuated upon the environment. Results indicate that NSGA-II is capable of producing feasible network topologies to satisfy maximum perimeter coverage, while reducing the energy required for topology reconfiguration. As far as we are concerned, this is the first time a RSN applied to a CIP scenario is self-organized in response to a risk analysis conducted on every sensor node on the basis of multiple risk features.
Starting Page	132
Ending Page	137
File Size	1276737
Page Count	6
File Format	PDF
e-ISBN	9781467347037
DOI	10.1109/CIVEMSA.2013.6617409
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-15
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Network topology Robot sensing systems Territorial security Batteries Topology Security Risk management Biological cells Critical infrastructure protection Robotic sensor networks Self-organization
Content Type	Text
Resource Type	Article

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