Modern infrastructure systems are becoming increasingly complex, interconnected, and reliant on digital control. While this enables efficiency and automation, it also introduces systemic vulnerabilities—exacerbated by cyber threats, geopolitical tensions, and environmental disruptions. Recent large-scale outages have demonstrated the societal and economic consequences of failures across energy, transport, industrial systems, and digital infrastructure.This paper explores how resilient edge computing can strengthen the dependability of critical infrastructure and consumer-facing networks. By enabling local data processing and autonomous decision-making, edge computing reduces reliance on centralized platforms, improves latency and availability, and supports continuity under degraded conditions.We outline key research directions in system architecture, distributed AI, secure communication, and governance frameworks—emphasizing interoperability, openness, and resilience as core design principles. The paper argues for coordinated efforts across research, policy, and industry to ensure that edge technologies can serve as a foundation for next-generation connected systems.

This paper presents key outcomes and insights from the DAIS (Distributed Artificial Intelligence Systems) project, a four-year European research initiative involving 47 partners across academia, industry, and the public sector. DAIS aimed to advance the deployment of scalable, trustworthy, and privacypreserving AI at the edge through a modular, federated architecture. The project introduced a layered approach spanning edge, fog, and cloud environments, supported by interoperable middleware platforms and co-designed hardware-software stacks. DAIS validated its technologies across a diverse set of realworld demonstrators in industrial automation, smart buildings, autonomous mobility, and emergency response. Key innovations include the deployment of federated learning on constrained edge devices, integration of analog AI hardware, and privacy-by-design inference pipelines. This paper summarizes the technical architecture, representative use cases, scientific highlights, integration challenges, and lessons learned. The findings offer actionable patterns for the design and deployment of Edge AI systems and inform future research and standardization priorities in the European digital ecosystem.

In smart electric grid systems, various sensors and Internet of Things (IoT) devices are used to collect electrical data at substations. In a traditional system, a multitude of energy-related data from substations needs to be migrated to central storage, such as Cloud or edge devices, for knowledge extraction that might impose severe data misuse, data manipulation, or privacy leakage. This motivates to propose anomaly detection system to detect threats and Federated Learning to resolve the issues of data silos and privacy of data. In this article, we present a framework to identify anomalies in industrial data that are gathered from the remote terminal devices deployed at the substations in the smart electric grid system. The anomaly detection system is based on Long Short-Term Memory (LSTM) and autoencoders that employs Mean Standard Deviation (MSD) and Median Absolute Deviation (MAD) approaches for detecting anomalies. We deploy Federated Learning (FL) to preserve the privacy of the data generated by the substations. FL enables energy providers to train shared AI models cooperatively without disclosing the data to the server. In order to further enhance the security and privacy properties of the proposed framework, we implemented homomorphic encryption based on the Paillier algorithm for preserving data privacy. The proposed security model performs better with MSD approach using HE-128 bit key providing 97% F1-score and 98% accuracy for K=5 with low computation overhead as compared with HE-256 bit key.

Traffic safety applications and other communication systems for vehicles together with data collection sensors have the potential to improve road safety. For this to be viable however, it is important that the data collection and communication can be trusted so that erroneous or malicious data does not impact the use cases of the applications. This paper studies current and upcoming solutions to such problems and how they can be modified and applied to meet both technical requirements as well as the needs of relevant stakeholders. The paper defines the TruVeLedger framework using technology from the fields of distributed ledgers and vehicular ad hoc networks (VANETs) to create a trusted platform. The paper considers the viability of different approaches to such a platform as well as defining a verifiable trusted communication protocol for vehicular networks.

This paper outlines the tradeoffs involved in utilizing Information-Centric Networking (ICN) for Internet of Things (IoT) scenarios. It describes contexts and applications where the IoT would benefit from ICN, and where a host-centric approach would be better. Requirements imposed by the heterogeneous nature of IoT networks are discussed in terms of connectivity, power availability, computational and storage capacity. Design choices are then proposed for an IoT architecture to handle these requirements, while providing efficiency and scalability. An objective is to not require any IoT specific changes of the ICN architecture per se, but we do indicate some potential modifications of ICN that would improve efficiency and scalability for IoT and other applications.

Exploring a large area can be conveniently performed by a team of small autonomous vehicles for different applications, such as search and rescue, cleaning, or lawn mowing. The efficiency and performance of such autonomous exploration depends on the exploration algorithm implemented by the vehicles, and can be enhanced with a better communication and collaboration strategy within the team. In this paper, a new algorithm is proposed and evaluated where vehicles with a limited communication range pro-actively seek their teammates to exchange information about the explored area. Simulations show that this approach allows the vehicles to finish the exploration and return to their base station 18% faster, without consuming more energy.

The number of mobile devices is estimated to now exceed the world's population, using more and more cloud services, and hence generating more and more traffic. Smartphones generate 95% of the total global handset traffic, and while approximately half of this traffic is sent to cellular networks, other handsets such as tablets are also using increasingly the cellular networks. This paper provides a closer look at the traffic generated on cellular networks by exploring billions of HTTP requests sent by millions of users to a nation-wide cellular network during 41 days. We confirm that - as in many other contexts - 20% of the users are responsible for more than 80% of the requests and provide a deeper analysis of the cellular network usage. Furthermore, we characterise the activity of users on their mobile device and which cloud services they use. For instance, almost 30% of the users use the cellular network frequently, mainly using search services and social networks, but 20% of their requests are sent to advertisement and tracking systems.

Mobile devices are now part of our everyday lives, and the emergence of online application marketplaces allow a rapid spread of new mobile applications to a large user base. Such user-installed mobile applications constitute a large part of our daily interaction with the devices. With more than one million available applications, Android Market, the online catalog for Android devices allows users to choose and download a large selection of disparate applications. Analysing and characterising the application marketplace download patterns provides a better insight on the needs and behaviour of users In this paper, we explore a large dataset collected by a major European telecom operator to study the downloads of Android applications on a nationwide scale. Our findings include that more than 43% of the application data downloaded is for games, and that a set of only 10 GB of applications is responsible for 88% of the 45 TB downloaded in total by all the users.

Information-Centric Networking (ICN) is an alternative architecture for computer networks, where the communication is focused on the data being transferred instead of the communicating hosts. This paper describes a demo of an experience sharing application for mobile phones built on an ICN platform designed for devices with intermittent connectivity. In particular, we detail how this application will be showcased in an indoor exhibition where experience is shared with media content that is geo-tagged using Bluetooth beacons and spread opportunistically to other users.

Traffic from wireless and mobile devices is expected to soon exceed traffic from fixed devices. Understanding the behaviour of users on mobile devices is important in order to improve the offered services and the provision of the underlying network. Globally, more than 60% of consumer Internet traffic is estimated to be video traffic, and the most popular video website, YouTube, estimates that mobile access makes up nearly 40% of the global watch time. This paper presents the first work to study the characteristics of YouTube user requests on a nationwide cellular network. This study is based on the analysis of a large dataset generated by 3 million users and collected by a major telecom operator. We show for instance that 20% of the users generate 78% of the requests, and that over 80% of the requests target only 20% of the distinct videos accessed during the data collection period. Our results provide a comprehensive insight into the way people use YouTube on mobile devices, and show a very high potential for video cacheability on the cellular network.

We describe early results from a program of experiments to characterize battery operation in the WSN regime.

Information or content centric networking is believed by many to have great potential to be the appropriate networking paradigm for the future Internet. In information centric networking, focus is shifted from the end-points in the network to the information objects themselves, with less care being placed on from where the information is fetched. In addition to the benefits this networking paradigm has in fixed networks, it also simplifies operation in mobile networks and has the potential to improve performance. In this paper, we describe one way in which the NetInf network architecture can be used in a hybrid mobile network in an urban setting, and run simulations to evaluate the benefits that this approach can yield, both to the end users (in terms of improved performance such as reduced latency with over 50%), as well as to the operators in terms of a reduction of traffic load in the cellular access networks with up to 97%.

Sensor networks are now enabling the monitoring of various environmental phenomena with more accuracy than the previous labour intensive and less technological solutions. This paper is concerned with the application of opportunistic networking techniques to wildlife monitoring, where the sensors are attached to animals moving in their habitat. We present seal-2-seal, a novel protocol for logging of node (i.e., animal) contacts in mobile networks and for dissemination of that information to sinks for further analysis. The protocol utilises an efficient data summary mechanism to reduce the amount of information that needs to be transmitted, thus reducing energy consumption. To evaluate the performance of the protocol, we implemented it for the Contiki operating system on sensor devices and ran simulations based on real-life mobility traces using the Cooja emulator.

T he SNetwork Connectivity (SNC) project works to enable Internet connectivity for the S´ ami population of reindeer herders in the Laponia region in northern Sweden. In this area, no infrastructure and thus, no Internet connec- tivity is normally available. Thus, DTN functionality is used to enable connectivity through the use of mobile relays. This paper describes a deployment and field test done within the SNC project, in which a Delay-Tolerant Networking system was deployed in the target region. Tests were run of the PRoPHET routing protocol, and three different applications were deployed and tested sucessfully. I. INTRODUCTION This paper describes a real-life deployment of a Delay Tol- erant Networking (DTN) system, and the experiences gained from that deployment. During a week in August 2006, the S´ ami Network Connectivity (SNC) project conducted a field test in the mountains of the Laponia region in the north of Sweden. The technological solution that was tested during this week had been the work of 2.5 years of the SNC project. The SNC project focuses on establishing Internet communication for the S´ ami population of reindeer herders, who live in remote areas, and relocate their base in accordance with a yearly cycle dictated by the natural behavior of reindeer. This population currently does not have reliable wired, wireless or satellite communication capabilities in major areas within which they work and live (or would prefer to stay if possible).

As wireless networks become more prevalent, users will demand the same applications that are currently available in wired networks. Further, they will expect to receive a quality of service similar to that obtained in a wired network. Included in these applications are real-time applications such as voice over IP and multimedia streams. To enable the support of applications that require real-time communication in ad hoc networks, congestion must be prevented so that the needed quality of service can be provided. An admission control mechanism is an essential component of the quality of service solution. Unfortunately, current admission control solutions encounter problems during mobility, often resulting in unacceptable disruptions in communication. To solve this problem, we apply multi-path routing mechanisms that maintain alternate paths to the destination and propose a new admission control protocol. We show through simulation that our solution is able to prevent communication disruptions and meet the QoS needs of applications better than previous solutions.