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Rute C. Sofia

Publications and source records attributed to Rute C. Sofia.

16 recordsLinked to original sources

White paper: A perspective on civilian-to-defence research transfer to SDD

Military capability is increasingly determined by software. Yet defence platforms are procured on decade-long timescales, while the software and AI models they carry must evolve in days or hours. This paper calls this mismatch the lifecycle paradox, and argues it is the central problem Software-Defined Defence (SDD) must solve. SDD rests on three dimensions: software and systems engineering (design, procurement, certification), AI engineering (sovereignty and trust of learned components), and connectivity and infrastructure engineering (timely exchange of information among sensors, AI, and operators). The proposed path to resilient SDD starts from civilian technologies, addressed through a continuous, DevOps-style loop: model-based systems engineering and simulation-based testing front-load design and verification; tactical connectivity and low-power edge execution carry that design into contested operation; continuous compliance, assurance, and variability management run as cross-cutting concerns. This loop is sustainable given capabilities already proven in automotive, manufacturing, space, and energy. The next step is validating them under adversarial or defence-certified conditions, with short-, medium-, and long-term paths to closing gaps. Closing the SDD gap while preserving civic benefits is a distributed responsibility: researchers must redirect methods toward adversarial conditions; industry must expose tooling to operational needs; policymakers must shape regulatory instruments; and defence agencies must validate results with operators. Recommendations span three horizons: a short-term baseline of adversarial testing and connectivity pilots; a medium-term pipeline of incremental certification; and a long-term validation closing the loop under operational conditions.

cs.SE

Performance Evaluation of Automated Multi-Service Deployment in Edge-Cloud Environments with the CODECO Toolkit

Containerized microservices are widely adopted for latency-sensitive and compute-intensive applications, with Kubernetes (K8s) as the dominant orchestration platform. However, automating the deployment and management of multi-service applications remains challenging, particularly in heterogeneous Edge-Cloud environments. This paper evaluates the CODECO toolkit, an open-source framework designed to enhance container orchestration across distributed infrastructures. We compare CODECO with baseline K8s workflows using three key performance indicators: deployment time, level of manual intervention, and runtime performance with resource utilization. Experiments across diverse hardware platforms (ARM, AMD, RPi) and K8s distributions, including lightweight variants such as k3s, demonstrate that CODECO substantially reduces manual effort while maintaining competitive performance and acceptable overhead. These results validate CODECO as an effective solution for Edge-Cloud orchestration and highlight its potential to improve the flexibility and intelligence of K8s-based deployments.

cs.DC

Building a Low-cost Network Digital Twin for the IoT-Edge-Cloud Continuum Using Open-Source Tooling

Validating network configurations and testing failure scenarios in IoT-edge-cloud environments without disrupting live infrastructure remains an open operational challenge. This paper presents a low-cost, fully open-source Network Digital Twin (NDT) for IIoT edge deployments, built on Containerlab, Open vSwitch, ONOS, and a Prometheus+Grafana observability stack. The framework integrates container-native topology emulation, SDN-driven traffic engineering, and real-time telemetry in a single deployable artefact. Validation against a physical Raspberry Pi edge WLAN shows strong distributional convergence on RTT median (delta = 0.4 ms) and UDP throughput (delta = 0.03 Mbps). Remaining divergences on TCP throughput and packet loss are attributed to identifiable virtualisation artefacts, with root causes and remediation paths provided.

cs.NI

Exploratory Analysis of Wi-Fi 6 Dynamic Resource Unit Sharing in Small-Scale Network Scenarios

This paper investigates dynamic Resource Unit (RU) allocation strategies for Wi-Fi~6 (IEEE 802.11ax) networks integrated with Time-Sensitive Networking (TSN), targeting the limitations of static RU scheduling under dynamic traffic conditions. We propose a dynamic RU allocation algorithm that maps TSN traffic classes to Wi-Fi~6 Quality of Service (QoS) mechanisms, including Enhanced Distributed Channel Access (EDCA) and aligns TSN control with Ethernet-based TSN domains. The proposed solution is evaluated using the ns-3 DetNetWiFi framework developed by fortiss, focusing on time-sensitive traffic. Simulation results demonstrate improved network efficiency with reductions in latency, jitter, and packet loss compared to static RU allocation schemes. These findings highlight the potential of dynamic RU allocation to support deterministic communication requirements in Wi-Fi~6-based TSN deployments and to enhance the reliability of hybrid industrial networks.

cs.NI

Greenness-Driven Scheduling in Far Edge Kubernetes: A CODECO Evaluation

Energy consumption is an increasing concern in IoT-Edge-Cloud infrastructures, where containerized application orchestration must balance performance with sustainability. This paper investigates how the Kubernetes CODECO framework integrates cross-layer energy-awareness into scheduling decisions for containerized applications across the IoT-Edge-Cloud continuum. CODECO monitors energy at both the computational level, via Kepler, and at a network (IP) level, and uses these metrics to define greenness heuristics that guide pod placement decisions through its ILP-based scheduler. The approach is experimentally evaluated on a real-world far Edge testbed composed of ARM-based embedded devices, comparing CODECO against vanilla Kubernetes across multiple scenarios. The results show that CODECO consistently reduces the energy consumption of the cluster, with savings of up to 11.01 mJ in computational energy and 4.14 mJ in network transmission energy consumption at peak load, for a wide set of scenarios which combine different types of injected fault conditions, including CPU stress, asymmetric network delay, and bandwidth contention. A composite greenness score combining both energy dimensions provides a stable and consistent ranking of scheduling strategies across all conditions, demonstrating its suitability as a unified energy indicator for cluster-level orchestration decisions across the IoT-Edge-Cloud continuum.

cs.NI

Towards Scalable Federated Container Orchestration: The CODECO Approach

This paper presents CODECO, a federated orchestration framework for Kubernetes that addresses the limitations of cloud-centric deployment. CODECO adopts a data-compute-network co-orchestration approach to support heterogeneous infrastructures, mobility, and multi-provider operation. CODECO extends Kubernetes with semantic application models, partition-based federation, and AI-assisted decision support, enabling context-aware placement and adaptive management of applications and their micro-services across federated environments. A hybrid governance model combines centralized policy enforcement with decentralized execution and learning to preserve global coherence while supporting far Edge autonomy. The paper describes the architecture and core components of CODECO, outlines representative orchestration workflows, and introduces a software-based experimentation framework for reproducible evaluation in federated Edge-Cloud infrastructure environments.

cs.DC

Should AI Become an Intergenerational Civil Right?

Artificial Intelligence (AI) is rapidly becoming a foundational layer of social, economic, and cognitive infrastructure. At the same time, the training and large-scale deployment of AI systems rely on finite and unevenly distributed energy, networking, and computational resources. This tension exposes a largely unexamined problem in current AI governance: while expanding access to AI is essential for social inclusion and equal opportunity, unconstrained growth in AI use risks unsustainable resource consumption, whereas restricting access threatens to entrench inequality and undermine basic rights. This paper argues that access to AI outputs largely derived from publicly produced knowledge should not be treated solely as a commercial service, but as a fundamental civil interest requiring explicit protection. We show that existing regulatory frameworks largely ignore the coupling between equitable access and resource constraints, leaving critical questions of fairness, sustainability, and long-term societal impact unresolved. To address this gap, we propose recognizing access to AI as an \emph{Intergenerational Civil Right}, establishing a legal and ethical framework that simultaneously safeguards present-day inclusion and the rights of future generations. Beyond normative analysis, we explore how this principle can be technically realized. Drawing on emerging paradigms in IoT--Edge--Cloud computing, decentralized inference, and energy-aware networking, we outline technological trajectories and a strawman architecture for AI Delivery Networks that support equitable access under strict resource constraints. By framing AI as a shared social infrastructure rather than a discretionary market commodity, this work connects governance principles with concrete system design choices, offering a pathway toward AI deployment that is both socially just and environmentally sustainable.

cs.CY

Experimenting with Energy-Awareness in Edge-Cloud Containerized Application Orchestration

This paper explores the role of energy-awareness strategies into the deployment of applications across heterogeneous Edge-Cloud infrastructures. It proposes methods to inject into existing scheduling approaches energy metrics at a computational and network level, to optimize resource allocation and reduce energy consumption. The proposed approach is experimentally evaluated using a real-world testbed based on ARM devices, comparing energy consumption and workload distribution against standard Kubernetes scheduling. Results demonstrate consistent improvements in energy efficiency, particularly under high-load scenarios, highlighting the potential of incorporating energy-awareness into orchestration processes for more sustainable cloud-native computing.

cs.NI

White paper: Towards Human-centric and Sustainable 6G Services -- the fortiss Research Perspective

As a leading research institute in software-intensive systems, fortiss is actively shaping the vision of Sixth Generation Mobile Communication (6G). Our mission is to ensure that 6G technologies go beyond technical advancements and are aligned with societal needs. fortiss plays a key role in 6G initiatives worldwide, including contributions to standardization bodies and collaborative Research and Development programs. We focus on software-defined, AI-enabled, and sustainable communication services that prioritize human values and long-term impact. 6G will redefine digital connectivity through cognitive intelligence, decentralized orchestration, and sustainability-oriented architectures. As expectations rise for ultra-reliable low-latency communication (URLLC) and personalized digital services, 6G must outperform prior generations. It will rely on AI-native networking, Edge-Cloud resource orchestration, and energy-aware data frameworks, ensuring both technical performance and societal relevance. This white paper presents the fortiss vision for a human-centric, sustainable, and AI-integrated 6G network. It outlines key research domains such as semantic communication, green orchestration, and distributed AI, all linked to societal and technological challenges. The white paper is aimed at researchers, industry experts, policymakers, and developers. It articulates the strategic direction and contributions of fortiss to 6G, emphasizing responsible innovation and interdisciplinary collaboration toward a meaningful 2030 vision.

cs.NI

Guidelines Towards Information-driven MobilityManagement

The architectural semantics of \emph{Information-Centric Networking} bring in interesting features in regards to mobility management: Information-Centric Networking is content-oriented, connection-less, and receiver-driven. Despite such intrinsic advantages, the support for node movement is being based on the principles of IP solutions. IP-based solutions are, however, host-oriented, and Information-Centric Networking paradigms are information-oriented. By following IP mobility management principles, some of the natural mobility support advantages of Information-Centric Networking are not being adequately explored. This paper contributes with an overview on how Information-Centric Networking paradigms handle mobility management as of today, highlighting current challenges and proposing a set of design guidelines to overcome them, thus steering a vision towards a content-centric mobility management approach.

cs.NI

A Discussion on Context-awareness to BetterSupport the IoT Cloud/Edge Continuum

This paper debates on notions of context-awareness as a relevant asset of networking and computing architectures for an Internet of Things (IoT), in particular in regards to a smoother support of the the networking operation between Cloud and Edge. Specifically, the paper debates on notions of context-awareness and goes over different types of context-awareness indicators that are being applied to Edge selection algorithms, covering the approaches currently used, the role of the algorithms applied, their scope, and contemplated performance metrics. Lastly, the paper provides guidelines for future research in the context of Cloud-Edge and the application of context-awareness to assist in a higher degree of automation of the network and, as consequence, a better support of the Cloud to Edge continuum.

cs.NI

An Analysis of Fog Computing Data Placement Algorithms

This work evaluates three Fog Computing dataplacement algorithms via experiments carried out with theiFogSim simulator. The paper describes the three algorithms(Cloud-only, Mapping, Edge-ward) in the context of an Internetof Things scenario, which has been based on an e-Health systemwith variations in applications and network topology. Resultsachieved show that edge placement strategies are beneficial toassist cloud computing in lowering latency and cloud energyexpenditure.

cs.NI

A tool to estimate roaming behavior in wireless architectures

This paper describes a software-based tool that tracks mobile node roaming and infers the time-to-handover as well as the preferential handover target, based on behavior inference solely derived from regular usage data captured in visited wireless networks. The paper presents the tool architecture; computational background for mobility estimation; operational guidelines concerning how the tool is being used to track several aspects of roaming behavior in the context of wireless networks. Target selection accuracy is validated having as baseline traces obtained in realistic scenarios.

cs.NI

NSense: A People-centric, non-intrusive Opportunistic Sensing Tool for Contextualizing Nearness

In the context of social well-being and context awareness several eHealth applications have been focused on tracking activities, such as sleep or specific fitness habits, with the purpose of promoting physical well-being with increasing success. Sensing technology can, however, be applied to improve social well-being, in addition to physical well-being. This paper addresses NSense, a tool that has been developed to capture and to infer social interaction patterns aiming to assist in the promotion of social well-being. Experiments carried out under realistic settings validate the NSense performance in terms of its capability to infer social interaction context based on our proposed computational utility functions. Traces obtained during the experiments are available via the CRAWDAD international trace repository.

cs.NI

Moving Towards a Socially-Driven Internet Architectural Design

This paper provides an interdisciplinary perspective concerning the role of prosumers on future Internet design based on the current trend of Internet user empowerment. The paper debates the prosumer role, and addresses models to develop a symmetric Internet architecture and supply-chain based on the integration of social capital aspects. It has as goal to ignite the discussion concerning a socially-driven Internet architectural design.

cs.CY

A Discussion on Developing Multihop Routing Metrics Sensitive to Node Mobility

This paper is focused on a discussion of parameters and heuristics that are expected to assist multihop routing in becoming more sensitive to node mobility. We provide a discussion concerning existing and a few proposed parameters. Moreover, the work also discusses two new heuristics based on the notion of link duration. The heuristics are compared based on a meaningful set of scenarios that attain different mobility aspects.

cs.NI