The ROC team is organizing two seminars delivered by Francesca Cuomo and Tiziana Cattai from Università la Sapienza, Roma 1 on september 20 at 10 a.m.

Room: amphi Friedman, 2 rue conté, 33.2 (stair 33, floor 2).

Title: Towards Edge Computing in LoRaWAN: new architectural models and future applications

Speaker: Francesca Cuomo, Università la Sapienza, Roma I


LoRaWAN networks have become a popular choice for enabling long-range, low-power connectivity in IoT applications. However, traditional LoRaWAN networks typically rely on a centralized architecture, which may pose limitations in terms of scalability, reliability, and adaptability. In contrast, decentralized LoRaWAN networks offer a compelling alternative with several distinct features.

This seminar deals with the advantages of decentralized LoRaWAN networks over their centralized counterparts, highlighting their potential to revolutionize the landscape of edge computing. By distributing intelligence and decision-making closer to the network’s edge, decentralized LoRaWAN networks enable faster data processing, reduced latency, and enhanced scalability.

One area ripe for innovation is security, where decentralized LoRaWAN networks offer robust protection against potential attacks and data breaches. With critical data processed and secured locally, the risk of single points of failure diminishes, leading to a more resilient and tamper-resistant system. Moreover, a prompt analysis of data streams at the edge plays a pivotal role in ensuring a quick reaction to attacks and other security issues. By processing data closer to the source, decentralized LoRaWAN networks facilitate real-time monitoring and detection of potential threats, significantly reducing response times compared to traditional centralized systems.

Traffic management represents another domain benefiting from decentralized LoRaWAN networks. As the volume of data generated by IoT devices increases, conventional centralized approaches may struggle to cope with the immense data flow. However, by leveraging edge computing, traffic can be efficiently managed, optimized, and localized, reducing the burden on the central infrastructure and ensuring efficient utilization of network resources.

As we explore these new horizons, several exciting applications emerge, promising to transform various industries like energy and water utilities, smart cities and e-health.


FRANCESCA CUOMO is Full Professor at Sapienza University of Rome teaching courses in Telecommunications, Network Infrastructures and Smart Environments. Prof. Cuomo has advised numerous master students in computer engineering, and has been the advisor of 13 PhD students in Networking. She is the Chair of the Master Degree in Data Science in Sapienza.

Her current research interests focus on Low Power Wide Area Networks and Internet of Things, 5G Networks, Vehicular networks and Sensor networks, Multimedia Networking, Energy saving in the Internet and in the wireless system.

She participated in several national and international research projects, being Principal Investigator of many on them. From May 2022 she is part of the Scientific Committee of the Fondazione Ugo Bordoni and member of the technical board of the Italian Internet Exchange Point NAMEX.

Francesca Cuomo has authored over 175 peer-reviewed papers published in prominent international journals and conferences. Her Google Scholar h-index is 31 with >4300 citations.

Relevant scientific international recognitions: 2 Best Paper Awards. She has been in the editorial board of Computer Networks (Elsevier) and now is member of the editorial board of the Ad-Hoc Networks (Elsevier), IEEE Transactions on Mobile Computing, Sensors (MDPI), Frontiers in Communications and Networks Journal. She has been the TPC co-chair of several editions of the ACM PE-WASUN workshop, TPC Co-Chair of ICCCN 2016, TPC Symposium Chair of IEEE WiMob 2017, General Co-Chair of the First Workshop on Sustainable Networking through Machine Learning and Internet of Things (SMILING), in conjunction with IEEE INFOCOM 2019; Workshop Co-Chair of AmI 2019: European Conference on Ambient Intelligence 2019. She is IEEE senior member.

Title: Graph model for Water Distribution Networks with IoT applications

Speaker: Tiziana Cattai, Università la Sapienza, Roma

Water Supply Systems (WSS) are made by physical connections that support the water flow, and sensors that measure it. In this configuration, sensor measures are acquired in a network and they are suitable to be analyzed as signals defined over a networked domain.

Smart Water Grids can be modeled as graphs, with links and nodes corresponding to pipes and sensors. Although graph theory and graph signal processing has been recently applied in  WSS, many open issues remain. In fact, there are no stable solutions for problems related to the IoT application, such as the number and the position of IoT sensors necessary to reconstruct the water flow in the network.
We propose a novel approach to derive an informative graph, where we represent the water flow as a Signal on Graph (SoG).  In this context, we develop a novel algorithm to reconstruct the graph signal in presence of missing values and we propose an original way to rank sensors in the network. Our framework enables us to have information about the number of sensors and their locations needed to reconstruct the flow with a fixed reconstruction error.

Tiziana Cattai received her bachelor and master degree at Sapienza University of Rome in Clinical and Biomedical Engineering respectively. She received a joint PhD from both Sorbonne Université and Sapienza University of Rome in Information and Communication Technologies. She is currently researcher at Sapienza University of Rome at the Department of Information Engineering, Electronics and Telecommunication. Her research interests include signal processing, graph signal processing and machine learning especially applied to water distribution networks and brain data.

Seminars on LoraWAN and Graph model for Water Distribution Networks by Francesca Cuomo and Tiziana Cattai – Sept. 20, 2023
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