EGU2020-18788, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-18788
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Resilience Enhancement of Communication Infrastructures

Sylvia Bach1, Mirjam Fehling-Kaschek2, and Sara Baldoni3
Sylvia Bach et al.
  • 1University of Wuppertal, School of Mechanical Engineering and Safety Engineering, Public Safety and Emergency Management, Germany (sbach@uni-wuppertal.de)
  • 2Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Efringen-Kirchen, Germany
  • 3RomaTre Universita degli Studi, Dpt. of Engineering, Rome, Italy

The Horizon2020 project RESISTO (Resilience enhancement and risk control platform for communication infrastructure operators) aims to reduce the risk as well as the impact of an anomalous incident for the telecommunication infrastructure. Incidents here can be natural hazards such as floods, earthquakes etc., but also cyber attacks, physical attacks or a combination of the latter two.

The approach uses a short-term control loop (STCL) that detects anomalies via various sensors or factors: internal remote sensors such as cameras, external sensing such as weather data, social media data mining, etc.. By doing so, the STCL is a risk predictor, but it also predicts effects of countermeasures and simulates short-term effects of failure with respect to performance degradation. This real-time risk and resilience assessment and the integrated interdependency analysis (among virtual and physical domains) lead to an effective Decision Support System (DSS) that detects critical situations and supports their management.

A risk and resilience analysis of the system is performed on a regular basis by the long term control loop (LTCL). It is used to generally evaluate the resilience of the system via network simulation techniques, to identify weak points and test effects of various improvement measures. The resilience management process is based on the risk management process defined in the ISO 31000 and refined to the specific needs of RESISTO. The outcome of the LTCL analysis can be compared to the measured values of the STCL to validate and improve the simulation model.

The functionality, modularity and adaptability of the DSS is validated by nine use cases with various sub-scenarios, led by the telecommunication providers in the consortium. The use cases apply differing combinations of real and virtual parts, posing a specific threat to the infrastructure. An example for the added value to the resilience and recovery strategies of a telecommunication infrastructure and its provider is given by a use case where an unspecified natural disaster hits a rural area:

Because the RESISTO system interfaces with specific national sensing platforms such as weather and seismic ones, it is aware of the natural disaster and its severity. Simultaneously, RESISTO receives the congestion events from the provider’s Network Management Center (NMC) and monitoring tools. It responds by “ordering” an Unmanned Aerial Vehicle (UAV) to make a damage inspection in the area. With the UAV, the platform identifies the affected critical network assets (antennas, switches, routers etc.) as the potential cause of the congestion, and correlates the loss of the network resources with the congestion events. RESISTO then suggests suitable mitigation actions, i.e. traffic redirection and or activation of auxiliary network resources. Also conceivable is the direct dispatch of technical / maintenance personnel, depending on safety aspects.

Telecommunication nowadays is crucial for the functioning of a society, on the corporate as well as on the private level. During the response and recovery phases of disasters, telecommunication infrastructures also play a central role. The RESISTO platform aims to be another step towards more resilient societies.

How to cite: Bach, S., Fehling-Kaschek, M., and Baldoni, S.: Resilience Enhancement of Communication Infrastructures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18788, https://doi.org/10.5194/egusphere-egu2020-18788, 2020

Comments on the presentation

AC: Author Comment | CC: Community Comment | Report abuse

Presentation version 1 – uploaded on 04 May 2020
  • CC1: decision systems, Maria Bostenaru Dan, 05 May 2020

    Thank you for sharing the presentation. My first question is about which funding scheme is this project in. I've seen several disasters related EU funded projects, but rather connected to urban areas and cultural heritage. However, common to all was that they were looking to ICT solutions for the DSS. 

    My own Marie Curie IEF (an FP6 project) was also looking to develop a DSS. Before I was in Germany in a research training network (called there Graduiertenkolleg) looking to economic efficiency, and for this I have already developped a decision tree. When I could chose my Marie Curie topic freely, I felt relieved that I don't have to do with economic questions anymore. The question of economic efficiency is generally less dealt with, therefore I would like to know more on the last slide, and on "cost evaluation [7]". But since before I had a course on "urban management, urban operations" by a professor coming from the US, I adapted that approach of management, which was a particular case of project management anyway required to write EU projects and dealing with decision resulted.

    The topic of decision is multifaceted. One can deal with it in decision trees, but one can go further, to the mentioned ICT supported systems (with corresponding ontologies to design the architecture) or to the mathematical models. Many papers in Mathematics (MDPI) deal with decision systems, for example fuzzyness. When assessing the impact of natural hazards, there is a fuzzyness, which could have been addressed in case of my first project by a Monte Carlo simulation which I haven't done. Then another approach to decision systems is looking to the methods employed (AHP, TOPSIS etc.). What do you use?

    Finally, I see that the presentation has different authors. I came for my second paper with more authors towards this, that I needed all their approval and I was late. It would be a good idea for me as well to include some papers with more/less authors, thank you for this idea.

    • AC1: Reply to CC1, Sylvia Bach, 08 May 2020

      For the first question, at this moment, we are not doing any cost evaluation. To do this in the future we would need more information from partners. Potentially we could use their SLAs (service level agreement) and SLOs (service level objectives) which relate the performance measures and the penalties operators face when they have not reached the required performance. Combining these and the performance time curves from step 6 could be a good start for a cost evaluation.

      For the second question regarding decision making process, decision support occurs in the short term control loop. The LTCL is offline, while the STCL is real time with direct response.

       

  • CC2: Methodological approach, Elena Petrova, 06 May 2020

    Thank you very much for sharing this presentation.

    My question: Your methodological approach includes 3 macro-scenarios. In your presentation, you explain Macro-scenario 1. What are the other two?

    • AC2: Reply to CC2, Sylvia Bach, 08 May 2020

      - Macro-Scenario 2: Interdependencies of providers of essential communication services - Interconnected CIs

      - Macro-Scenario 3: CI evolution towards the future 5G telecom CIs and networks and the emerging IoT world