21 research outputs found
Network Inspection for Detecting Strategic Attacks
This article studies a problem of strategic network inspection, in which a
defender (agency) is tasked with detecting the presence of multiple attacks in
the network. An inspection strategy entails monitoring the network components,
possibly in a randomized manner, using a given number of detectors. We
formulate the network inspection problem as a large-scale
bilevel optimization problem, in which the defender seeks to determine an
inspection strategy with minimum number of detectors that ensures a target
expected detection rate under worst-case attacks. We show that optimal
solutions of can be obtained from the equilibria of a
large-scale zero-sum game. Our equilibrium analysis involves both
game-theoretic and combinatorial arguments, and leads to a computationally
tractable approach to solve . Firstly, we construct an
approximate solution by utilizing solutions of minimum set cover (MSC) and
maximum set packing (MSP) problems, and evaluate its detection performance. In
fact, this construction generalizes some of the known results in network
security games. Secondly, we leverage properties of the optimal detection rate
to iteratively refine our MSC/MSP-based solution through a column generation
procedure. Computational results on benchmark water networks demonstrate the
scalability, performance, and operational feasibility of our approach. The
results indicate that utilities can achieve a high level of protection in
large-scale networks by strategically positioning a small number of detectors
Sensor placement for fault location identification in water networks: A minimum test cover approach
This paper focuses on the optimal sensor placement problem for the
identification of pipe failure locations in large-scale urban water systems.
The problem involves selecting the minimum number of sensors such that every
pipe failure can be uniquely localized. This problem can be viewed as a minimum
test cover (MTC) problem, which is NP-hard. We consider two approaches to
obtain approximate solutions to this problem. In the first approach, we
transform the MTC problem to a minimum set cover (MSC) problem and use the
greedy algorithm that exploits the submodularity property of the MSC problem to
compute the solution to the MTC problem. In the second approach, we develop a
new \textit{augmented greedy} algorithm for solving the MTC problem. This
approach does not require the transformation of the MTC to MSC. Our augmented
greedy algorithm provides in a significant computational improvement while
guaranteeing the same approximation ratio as the first approach. We propose
several metrics to evaluate the performance of the sensor placement designs.
Finally, we present detailed computational experiments for a number of real
water distribution networks
Flexible Reconfiguration of Existing Urban Water Infrastructure Systems
This paper presents a practical methodology for the flexible reconfiguration of existing water distribution infrastructure, which is adaptive to the water utility constraints and facilitates in operational management for pressure and water loss control. The network topology is reconfigured into a star-like topology, where the center node is a connected subset of transmission mains, that provides connection to water sources, and the nodes are the subsystems that are connected to the sources through the center node. In the proposed approach, the system is first decomposed into the main and subsystems based on graph theory methods and then the network reconfiguration problem is approximated as a single-objective linear programming problem, which is efficiently solved using a standard solver. The performance and resiliency of the original and reconfigured systems are evaluated through direct and surrogate measures. The methodology is demonstrated using two large-scale water distribution systems, showing the flexibility of the proposed approach. The results highlight the benefits and disadvantages of network decentralization.MIT-Technion Fellowshi
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