We consider the problem of deploying sensors in a large water distribution network, in order to detect the malicious introduction of contaminants. We show that a large class of realistic objective functions -such as reduction of detection time and the population protected from consuming contaminated water -exhibit an important diminishing returns effect called submodularity. We exploit the submodularity of these objectives in order to design efficient placement algorithms with provable performance guarantees. Our algorithms do not rely on mixed integer programming, and scale well to networks of arbitrary size. The problem instances considered in our approach are orders of magnitude (a factor of 72) larger than the largest problems solved in the literature. We show how our method can be extended to multicriteria optimization,
Krause et al. consider the problem of deploying sensors for detecting malicious contaminations in large-scale water-distribution networks REF .
Efficient sensor placement optimization for securing large water distribution networks
Journal of Water Resources Planning and Management
Engineering