arXiv subjects

Armir Bujari

Publications and source records attributed to Armir Bujari.

6 recordsLinked to original sources

arXiv2026

A Cloud Continuum Research Infrastructure for Distributed CPS Experimentation

Cloud Continuum applications require experimental environments capable of combining heterogeneous Edge, Fog, Cloud, and high-performance computing resources while preserving reproducibility, observability, and control over distributed deployments. This paper presents a two-level reference architecture for Cloud Continuum experimentation built on top of the SLICES Cloud Continuum Blueprint. The proposed approach separates the research-infrastructure layer, which exposes and manages distributed resources, from the application layer, where Cyber-Physical workflows are organized according to an Edge-Fog-Cloud pattern in which placement, timing, and data provenance are treated as first-class experimental concerns. The architecture is designed to support multiple continuum applications rather than a single domain-specific prototype. At the Edge, applications interact with physical devices and perform low-latency sensing or safety actions; at the Fog, they execute near-source coordination, mediation, and stream-processing logic; at the Cloud, they consolidate global knowledge through analytics, optimization, and visualization. This partitioning enables researchers to deploy, customize, and compare alternative control and monitoring strategies over the same programmable infrastructure substrate. The approach is validated through two representative use cases: Renewable Energy Community management, where distributed Digital Twin coordination and time-window-based energy control are requested, and AirWatch, a monitoring pipeline focused on anomaly detection, low-latency alerting, and cloud-side aggregation. Both workloads are evaluated through a systematic campaign of 40 runs comparing virtualized and physical edge deployments over a geographically distributed infrastructure.

cs.DC↗

arXiv2024

Empirical Application Insights on Industrial Data and Service Aspects of Digital Twin Networks

Digital twin networks (DTNs) serve as an emerging facilitator in the industrial networking sector, enabling the management of new classes of services, which require tailored support for improved resource utilization, low latencies and accurate data fidelity. In this paper, we explore the intersection between theoretical recommendations and practical implications of applying DTNs to industrial networked environments, sharing empirical findings and lessons learned from our ongoing work. To this end, we first provide experimental examples from selected aspects of data representations and fidelity, mixed-criticality workload support, and application-driven services. Then, we introduce an architectural framework for DTNs, exposing a more practical extension of existing standards; notably the ITU-T Y.3090 (2022) recommendation. Specifically, we explore and discuss the dual nature of DTNs, meant as a digital twin of the network and a network of digital twins, allowing the co-existence of both paradigms.

cs.NI↗

arXiv2023

A Layered Architecture Enabling Metaverse Applications in Smart Manufacturing Environments

The steady rollout of Industrial IoT (IIoT) technology in the manufacturing domain embodies the potential to implement smarter and more resilient production processes. To this end, it is expected that there will be a strong reliance of manufacturing processes on cloud/edge services so as to act intelligently and flexibly. While automation is necessary to handle the environment's complexity, human-in-the-loop design approaches are paramount. In this context, Digital Twins play a crucial role by allowing human operators to inspect and monitor the environment to ensure stability and reliability. Integrating the IIoT with the Metaverse enhances the system's capabilities even further, offering new opportunities for efficiency and collaboration while enabling integrated management of assets and processes. This article presents a layered conceptual architecture as an enabler for smart manufacturing metaverse environments, targeting real-time data collection and representations from shopfloor assets and processes. At the bottom layer, our proposal relies on middleware technology, serving differentiated Quality of Service (QoS) needs of the Operation Technology (OT) monitoring processes. The latter contributes to feeding a virtual layer where data processes reside, creating representations of the monitored phenomena at different timescales. Metaverse applications can consume data by tapping into the metaverse engine, a microservice-oriented and accelerated Platform as a Service (PaaS) layer tasked with bringing data to life. Without loss of generality, we profile different facets of our proposal by relying on two different proof-of-concept inspection applications aimed at real-time monitoring of the network fabric activity and a visual asset monitoring one.

cs.NI↗

arXiv2023

A Novel Design for Advanced 5G Deployment Environments with Virtualized Resources at Vehicular and MEC Nodes

IoT and edge computing are profoundly changing the information era, bringing a hyper-connected and context-aware computing environment to reality. Connected vehicles are a critical outcome of this synergy, allowing for the seamless interconnection of autonomous mobile/fixed objects, giving rise to a decentralized vehicle-to-everything (V2X) paradigm. On this front, the European Telecommunications Standards Institute (ETSI) proposed the Multi-Access Edge Computing (MEC) standard, addressing the execution of cloud-like services at the very edge of the infrastructure, thus facilitating the support of low-latency services at the far-edge. In this article, we go a step further and propose a novel ETSI MEC-compliant architecture that fully exploits the synergies between the edge and far-edge, extending the pool of virtualized resources available at MEC nodes with vehicular ones found in the vicinity. In particular, our approach allows vehicle entities to access and partake in a negotiation process embodying a rewarding scheme, while addressing resource volatility as vehicles join and leave the resource pool. To demonstrate the viability and flexibility of our proposed approach, we have built an ETSI MEC-compliant simulation model, which could be tailored to distribute application requests based on the availability of both local and remote resources, managing their transparent migration and execution. In addition, the paper reports on the experimental validation of our proposal in a 5G network setting, contrasting different service delivery modes, by highlighting the potential of the dynamic exploitation of far-edge vehicular resources.

cs.NI↗

arXiv2023

KuberneTSN: a Deterministic Overlay Network for Time-Sensitive Containerized Environments

The emerging paradigm of resource disaggregation enables the deployment of cloud-like services across a pool of physical and virtualized resources, interconnected using a network fabric. This design embodies several benefits in terms of resource efficiency and cost-effectiveness, service elasticity and adaptability, etc. Application domains benefiting from such a trend include cyber-physical systems (CPS), tactile internet, 5G networks and beyond, or mixed reality applications, all generally embodying heterogeneous Quality of Service (QoS) requirements. In this context, a key enabling factor to fully support those mixed-criticality scenarios will be the network and the system-level support for time-sensitive communication. Although a lot of work has been conducted on devising efficient orchestration and CPU scheduling strategies, the networking aspects of performance-critical components remain largely unstudied. Bridging this gap, we propose KuberneTSN, an original solution built on the Kubernetes platform, providing support for time-sensitive traffic to unmodified application binaries. We define an architecture for an accelerated and deterministic overlay network, which includes kernel-bypassing networking features as well as a novel userspace packet scheduler compliant with the Time-Sensitive Networking (TSN) standard. The solution is implemented as tsn-cni, a Kubernetes network plugin that can coexist alongside popular alternatives. To assess the validity of the approach, we conduct an experimental analysis on a real distributed testbed, demonstrating that KuberneTSN enables applications to easily meet deterministic deadlines, provides the same guarantees of bare-metal deployments, and outperforms overlay networks built using the Flannel plugin.

cs.NI↗

arXiv2020

Air Quality Control through Bike Sharing Fleets

Air quality and the presence of tiny particular matter are crucial factors in human health, especially when considering urban scenarios. In this context, smart mobility coupled with low-cost sensors can create a distributed and sustainable platform for social sensing able to provide pervasive data to citizens and public administrations. Sustainable and eco-aware decisions can then be supported by empirical evidence, resulting in an improved life and city administration. In this paper, we present ArduECO, a simple Arduino-based wireless device able of collecting air quality data. Without loss of generality, we have designed our device as a box that can be installed on a bike; in this way, beyond private bikes, municipalities could exploit their bike sharing fleets as pervasive sensing systems.

cs.NI↗