Special Issue on Smart City-Networks

Scope: In recent years, there is a growing interest on sustainable and smart cities in which advanced technologies for data collection and elaboration are being developed together with technologies for mitigating greenhouse gas emissions reduction (such as renewables, electric vehicles, high efficiency production plants, etc.). Cities need more efficient water, transportation, and energy systems to address various challenges including a growing population, environmental and economical sustainability, and resiliency to natural disasters and/or unpredicted events. This special issue focuses on smart city-networks, which we define to include networks of networks at multiple levels integrating multiple flows such as energy, physics, information.

Typical examples of smart city-networks are electrical distribution grids that are characterized by different nodes and/or clusters of microgrids, a transportation network in which roads represent links and crossings are nodes, communication networks, pipelines for water distribution systems, production and logistics systems distributed over the territory, buildings and microgrids that should be managed by an aggregator in the energy market, or combinations of such networks. Sometimes, such networks are interconnected and interacting: for example, charging stations for electric vehicles couple electric distribution and transportation networks, all physical networks are nowadays coupled with the communication network, water distribution and district heating, etc.

The increasing shift towards solutions consisting of automation, digitalization, and IoT (Internet of Things) necessitate a holistic management of several networks at the city level, so as to collect, monitor, and process large amounts of data, analyze and synthesize real-time control algorithms, carry-out large-scale case studies, and handle emergency situation. There is a compelling need for smart city-networks that enable a combined synergistic management of networks that deliver power, water, food, transportation, and communication.

Several features are common to these networks. In many of these networks, there’s an urgent concern related to sustainability, energy efficiency and low carbon footprint, which necessitate new tools, new methodologies, and new technologies. A typical example is a power network that includes renewable generation, storage systems, distributed and active loads (such as microgrids, electric vehicles, buildings, etc.), intelligent sensors and meters, and new market actors such as aggregators. Water networks are experiencing an evolution in terms of metering, monitoring, and remote control that open new challenges for advanced optimization and control approaches. Similar challenges are present in transportation, telecommunication, and natural gas networks. Another example is the need to understand the resilience properties of these networks when subjected to various hostile anomalies either due to natural disasters or adversarial cyber-attacks. In many cases, interdependence between these networks can itself be leveraged to lead to efficient, optimal, or resilient operation.

The focus of this special issue is to assemble new advances in the study of smart city-networks. Network control methods that enable optimization and resiliency constitute one example. The use of data-driven techniques, including many that are based on machine learning, is another. Graph- theoretic and game-theoretic solutions that help understand these networks and interface between these networks are essential. Tradeoffs regarding problems with smart city-networks (such as resiliency and privacy, performance and computational complexity of various algorithms, etc.) need to be suitably characterized. Challenges precipitated due to large amounts of data and the scale of these networks need to be addressed. Both theoretical and practical explorations of this topic are necessary.

The special issue focuses on novel methods, models and tools to enhance the current state of the art in this area and on the application of these methodologies in learning and control problems arising in smart networks.

Specific topics include (but not limited to)
  • Distributed control and optimization for smart city networks (traffic, transportation, water, energy, telecommunication, gas, smart grids, supply chains and production systems, etc.)
  • Fault detection and state estimation of water, transportation and energy networks
  • Machine learning-based control and optimization for smart city’s networks
  • Optimal control of smart city networks
  • Control, optimization, and communication interconnected Smart city networks
  • Resiliency and privacy of smart city networks
  • Issues related to big-data and their connection to analysis and synthesis of efficient networks
  • Cyber-physical security and cyber-physical human systems of large-scale networks
  • Applications to real smart city networks (water, energy, transportation, traffic, energy communities, etc.)
  • Applications to interconnected smart city networks (e.g., power grid and electric mobility, water networks and district heating, energy communities including smart buildings and distributed generation, integration with the ICT network, etc.)
Important Dates
  • Paper submission deadline: January 31, 2021
  • Completion of the first round review: July 2021
  • Completion of the second round review: December 2021
  • Final submission due: April 2022
  • Tentative publication date: June 2022

Submission Details

Information on the submission process and manuscript format can be found at: https://cemse.kaust.edu.sa/tcns/information-authors

Guest Editors

  • Michela Robba, Associate Professor, Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
  • Giulio Ferro, Assistant Researcher, PhD, Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
  • Rong Su, Associate Professor, School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore
  • Anuradha Annaswamy, Senior Research Scientist, Department of Mechanical Eng., Director, Active-adaptive Control Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA
  • Christos Cassandras, Professor, Head, Division of Systems Engineering, Center for Information and Systems Engineering (CISE), Boston University, Boston, MA
  • Karl Johansson, Professor, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden