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

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.