The faster the better: On the shortest paths role for near real-time decision making of water utilities

Abstract Near real-time monitoring and control of critical infrastructure is essential for the operation and management of cities in a world that is, today, more complex and interconnected than ever. Such an infrastructure can be represented as complex networks an some of their related indices and statistics, many of them based on the shortest paths, play a pivotal role in the decision making for public services such as internet, energy or water. Particularly, the literature has shown that shortest paths are key for resilience and criticality assessment in a water distribution systems (WDS). This paper proposes a procedure to speed-up the computation of shortest paths in a WDS, as it can straightforwardly benefit any critical infrastructure. The proposal is based on a reduced dimension of a complex network representing any critical infrastructure. Despite the consequent decrease in the number of all possible paths in the network, the main advantage and novelty of this proposal is to continue finding the exact solution for the shortest paths. Experimental results show that the procedure brings a computational-time reduction consistently over 50% and up to 90% in some cases. In addition, the paper reveals how the use of shortest paths benefits WDS operation and management, as well as playing a key role in near real-time contamination detection and leakage control.

[1]  David Hart,et al.  Impact of sensor detection limits on protecting water distribution systems from contamination events , 2005 .

[2]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Aristides Gionis,et al.  Fast shortest path distance estimation in large networks , 2009, CIKM.

[4]  P. Klein,et al.  Faster shortest-path algorithms for planar graphs , 1994, STOC '94.

[5]  Carlo Giudicianni,et al.  Topological Taxonomy of Water Distribution Networks , 2018 .

[6]  Andreas Krause,et al.  Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks , 2008 .

[7]  Enrico Zio,et al.  The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures , 2009, Reliab. Eng. Syst. Saf..

[8]  Carlo Giudicianni,et al.  Automatic Multiscale Approach for Water Networks Partitioning into Dynamic District Metered Areas , 2019, Water Resources Management.

[9]  Robert E. Tarjan,et al.  Fibonacci heaps and their uses in improved network optimization algorithms , 1987, JACM.

[10]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[11]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[12]  Mark Crovella,et al.  Virtual landmarks for the internet , 2003, IMC '03.

[13]  Dragan Savic,et al.  Simplified Approach to Water Distribution System Management via Identification of a Primary Network , 2018 .

[14]  ZeadallySherali,et al.  Critical infrastructure protection , 2015 .

[15]  Laurence R. Rilett,et al.  Heuristic shortest path algorithms for transportation applications: State of the art , 2006, Comput. Oper. Res..

[16]  Mingyuan Zhang,et al.  Node vulnerability of water distribution networks under cascading failures , 2014, Reliab. Eng. Syst. Saf..

[17]  F. Archetti,et al.  A Graph based Analysis of Leak Localization in Urban Water Networks , 2014 .

[18]  Istvan Lippai Colorado Springs Utilities Case Study: Water System Calibration / Optimization , 2005 .

[19]  Leonardo Dueñas-Osorio,et al.  Exploring Topological Effects on Water Distribution System Performance Using Graph Theory and Statistical Models , 2017 .

[20]  Armando Di Nardo,et al.  A genetic algorithm for demand pattern and leakage estimation in a water distribution network , 2015 .

[21]  Jon M. Kleinberg,et al.  Triangulation and embedding using small sets of beacons , 2004, 45th Annual IEEE Symposium on Foundations of Computer Science.

[22]  Thambipillai Srikanthan,et al.  Heuristic techniques for accelerating hierarchical routing on road networks , 2002, IEEE Trans. Intell. Transp. Syst..

[23]  Sherali Zeadally,et al.  Critical infrastructure protection: Requirements and challenges for the 21st century , 2015, Int. J. Crit. Infrastructure Prot..

[24]  Vincent A. Traag,et al.  Faster unfolding of communities: speeding up the Louvain algorithm , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Maoguo Gong,et al.  An efficient shortest path approach for social networks based on community structure , 2016, CAAI Trans. Intell. Technol..

[26]  Joaquín Izquierdo,et al.  An approach to water supply clusters by semi-supervised learning , 2010 .

[27]  Santo Fortunato,et al.  Community detection in networks: A user guide , 2016, ArXiv.

[28]  Philip N. Klein,et al.  Faster Shortest-Path Algorithms for Planar Graphs , 1997, J. Comput. Syst. Sci..

[29]  Armando Carravetta,et al.  Zero-net energy management for the monitoring and control of dynamically-partitioned smart water systems , 2020 .

[30]  Sheng Huang,et al.  Incremental Sensor Placement Optimization on Water Network , 2013, ECML/PKDD.

[31]  Elke A. Rundensteiner,et al.  Hierarchical Encoded Path Views for Path Query Processing: An Optimal Model and Its Performance Evaluation , 1998, IEEE Trans. Knowl. Data Eng..

[32]  Anna Scaglione,et al.  Generating Statistically Correct Random Topologies for Testing Smart Grid Communication and Control Networks , 2010, IEEE Transactions on Smart Grid.

[33]  Avi Ostfeld,et al.  The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms , 2008 .

[34]  Enrico Creaco,et al.  Topological Placement of Quality Sensors in Water-Distribution Networks without the Recourse to Hydraulic Modeling , 2020 .

[35]  Sakti Pramanik,et al.  An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps , 2002, IEEE Trans. Knowl. Data Eng..