Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks

Abstract

The problem of deploying sensors in a large water distribution network is considered, in order to detect the malicious introduction of contaminants. It is shown that a large class of realistic objective functions-such as reduction of detection time and the population protected from consuming contaminated water-exhibits an important diminishing returns effect called submodularity. The submodularity of these objectives is exploited in order to design efficient placement algorithms with provable performance guarantees. The algorithms presented in this paper do not rely on mixed integer programming, and scale well to networks of arbitrary size. The problem instances considered in the approach presented in this paper are orders of magnitude ͑a factor of 72͒ larger than the largest problems solved in the literature. It is shown how the method presented here can be extended to multicriteria optimization, selecting placements robust to sensor failures and optimizing minimax criteria. Extensive empirical evidence on the effectiveness of the method presented in this paper on two benchmark distribution networks, and an actual drinking water distribution system of greater than 21,000 nodes, is presented.

Incremental Sensor Placement Optimization on Water Network

“…Submodularity was widely used in sensor placement optimization [22,25]. But these solutions are mostlybuilt for static water network.…”

“…In fact, according to previous works [25,16,17], it requires an exponential number of sensors to detect all scenarios in A, which is unaffordable in real world due to the limited budget. Hence, covering scenarios as many as possible under the budget limit is a more realistic objective for real applications.…”

Risk-Informed Monitoring, Verification and Accounting (RI-MVA). An NRAP White Paper Documenting Methods and a Demonstration Model for Risk-Informed MVA System Design and Operations in Geologic Carbon Sequestration

“…One historic focus has been on analytical frameworks for the design of sensor networks in drinking water distribution systems, with optimization objectives that include contamination detection times and sizes of affected populations [Ostfeld et al, 2006;Storck et al, 1997;Krause et al 2008]. National security is another domain that has made significant investment in developing methods to optimize sensor network designs [Zou and Chakrabarty, 2004].…”

Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms

“…Most of the previous works have addressed the sensor placement problem regarding contamination monitoring or model/demand calibration. For example, in [15,16], the problem of deploying sensors in a large water distribution network is considered in order to detect the malicious introduction of contaminants; or, in [17,18], the problem of sensor placement for model and demand calibration, respectively, is addressed. On the other hand, less work has been carried out regarding sensor placement for leak location.…”