SearcharxivSearch

arXiv subjects

Pablo Muñoz

Publications and source records attributed to Pablo Muñoz.

13 recordsLinked to original sources

Performance Analysis of 5G RAN Slicing Deployment Options in Industry 4.0 Factories

This paper studies Radio Access Network (RAN) slicing strategies for 5G Industry~4.0 networks with ultra-reliable low-latency communication (uRLLC) requirements. We compare four RAN slicing deployment options that differ in slice sharing and in the degree of per-line or per-flow isolation. Unlike prior works that assume a fixed slicing structure, this work addresses how RAN slicing should be instantiated in the presence of multiple production lines and heterogeneous industrial flows. A Stochastic Network Calculus (SNC)-based analytical framework and a heuristic slice planner are used to evaluate per-flow delay guarantees and radio resource utilization. Within the considered RAN-level analytical model, the results show that, under resource scarcity, only per-flow slicing prevents delay violations, whereas slice-sharing and hybrid deployments improve aggregation efficiency at the cost of weaker protection for the most delay-critical flows. Execution-time results show that the proposed planner operates at non-real-time (Non-RT) time scales, supporting its implementation as an rApp within Open RAN (O-RAN) Non-RT RAN Intelligent Controller (RIC) control loops.

cs.NI

Impact of 5G Latency and Jitter on TAS Scheduling in a 5G-TSN Network: An Empirical Study

Deterministic communications are essential to meet the stringent delay and jitter requirements of Industrial Internet of Things (IIoT) services. IIoT increasingly demands wide-area wireless mobility to support Autonomous Mobile Robots (AMR) and dynamic workflows. Integrating Time-Sensitive Networking (TSN) with 5G private networks is emerging as a promising approach to fulfill these requirements. In this architecture, 5G provides wireless access for industrial devices, which connect to a TSN backbone that interfaces with the enterprise edge/cloud, where IIoT control and computing systems reside. TSN achieves bounded latency and low jitter using IEEE 802.1Qbv Time-Aware Shaper (TAS), which schedules the network traffic in precise time slots. However, the stochastic delay and jitter inherent in 5G disrupt TSN scheduling, requiring careful tuning of TAS parameters to maintain end-to-end determinism. This paper presents an empirical study evaluating the impact of 5G downlink delay and jitter on TAS scheduling using a testbed with TSN switches and a commercial 5G network. Results show that guaranteeing bounded latency and jitter requires careful setting of TAS transmission window offset between TSN switches based on the measured 5G delay bounded by a high order p-th percentile. Otherwise, excessive offset may cause additional delay or even a complete loss of determinism.

cs.NI

Empirical Evaluation of a 5G Transparent Clock for Time Synchronization in a TSN-5G Network

Time synchronization is essential for industrial IoT and Industry 4.0/5.0 applications, but achieving high synchronization accuracy in Time-Sensitive Networking (TSN)-5G networks is challenging due to jitter and asymmetric delays. 3GPP TS 23.501 defines three 5G synchronization modes: time-aware system, boundary clock (BC), and transparent clock (TC), where TC offers a promising solution. However, to the best of our knowledge, there is no empirical evaluation of TC in a TSN-5G network. This paper empirically evaluates an 5G end-to-end TC in a TSN-5G network, implemented on commercial TSN switches with a single clock. For TC development, we compute the residence time in 5G and recover the clock domain at the slave node. We deploy a TSN-5G testbed with commercial equipment for synchronization evaluation by modifying the Precision Timing Protocol (PTP) message transmission rates. Experimental results show a peak-to-peak synchronization of 500 ns, meeting the industrial requirement of < 1 us, with minimal synchronization offsets for specific PTP message transmission rates.

cs.NI

Unleashing 5G Seamless Integration with TSN for Industry 5.0: Frame Forwarding and QoS Treatment

Integrating Time-Sensitive Networking (TSN) and 5th Generation (5G) systems is key for providing wireless low-latency services in industry. Despite research efforts, challenges remain. Due to the lack of commercial 5G modems supporting Ethernet-based sessions, tunneling mechanisms must be used to enable Layer 2 connectivity between TSN islands via IP-based 5G modems. Furthermore, harmonizing traffic classification and prioritization between TSN and 5G technologies is crucial for meeting industrial service requirements. In this work, we propose a Virtual Extensible LAN (VxLAN)-based solution to harmonize frame forwarding and Quality of Service (QoS) treatment among 5G and TSN. Our solution supports multiple Virtual Local Area Networks (VLANs) across several production lines. Furthermore, it supports TSN traffic mapping into 5G QoS flows. We use a 5G testbed to validate the effectiveness of the adopted solution. Our results show the average delay introduced by the proposed mechanisms is approximately 100 μs, which is significantly lower than the typical 5G packet transmission delay. Moreover, our findings demonstrate our solution preserves QoS treatment between the 5G system and TSN, ensuring that the priority of 5G QoS flows aligns with the priorities of industrial traffic flows.

cs.NI

Empirical Analysis of 5G TDD Patterns Configurations for Industrial Automation Traffic

The digital transformation driven by Industry 4.0 relies on networks that support diverse traffic types with strict deterministic end-to-end latency and mobility requirements. To meet these requirements, future industrial automation networks will use time-sensitive networking, integrating 5G as wireless access points to connect production lines with time-sensitive networking bridges and the enterprise edge cloud. However, achieving deterministic end-to-end latency remains a challenge, particularly due to the variable packet transmission delay introduced by the 5G system. While time-sensitive networking bridges typically operate with latencies in the range of hundreds of microseconds, 5G systems may experience delays ranging from a few to several hundred milliseconds. This paper investigates the potential of configuring the 5G time division duplex pattern to minimize packet transmission delay in industrial environments. Through empirical measurements using a commercial 5G system, we evaluate different TDD configurations under varying traffic loads, packet sizes and full buffer status report activation. Based on our findings, we provide practical configuration recommendations for satisfying requirements in industrial automation, helping private network providers increase the adoption of 5G.

cs.NI

Empirical Analysis of the Impact of 5G Jitter on Time-Aware Shaper Scheduling in a 5G-TSN Network

Deterministic communications are essential for industrial automation, ensuring strict latency requirements and minimal jitter in packet transmission. Modern production lines, specializing in robotics, require higher flexibility and mobility, which drives the integration of Time-Sensitive Networking (TSN) and 5G networks in Industry 4.0. TSN achieves deterministic communications by using mechanisms such as the IEEE 802.1Qbv Time-Aware Shaper (TAS), which schedules packet transmissions within precise cycles, thereby reducing latency, jitter, and congestion. 5G networks complement TSN by providing wireless mobility and supporting ultra-Reliable Low-Latency Communications. However, 5G channel effects such as fast fading, interference, and network-induced latency and jitter can disrupt TSN traffic, potentially compromising deterministic scheduling and performance. This paper presents an empirical analysis of 5G network latency and jitter on IEEE 802.1Qbv performance in a 5G-TSN network. We evaluate the impact of 5G integration on TSN's deterministic scheduling through a testbed combining IEEE 802.1Qbv-enabled switches, TSN translators, and a commercial 5G system. Our results show that, with proper TAS configuration in the TSN switch aligned with the 5G system, jitter can be mitigated, maintaining deterministic performance.

cs.NI

BRATI: Bidirectional Recurrent Attention for Time-Series Imputation

Missing data in time-series analysis poses significant challenges, affecting the reliability of downstream applications. Imputation, the process of estimating missing values, has emerged as a key solution. This paper introduces BRATI, a novel deep-learning model designed to address multivariate time-series imputation by combining Bidirectional Recurrent Networks and Attention mechanisms. BRATI processes temporal dependencies and feature correlations across long and short time horizons, utilizing two imputation blocks that operate in opposite temporal directions. Each block integrates recurrent layers and attention mechanisms to effectively resolve long-term dependencies. We evaluate BRATI on three real-world datasets under diverse missing-data scenarios: randomly missing values, fixed-length missing sequences, and variable-length missing sequences. Our findings demonstrate that BRATI consistently outperforms state-of-the-art models, delivering superior accuracy and robustness in imputing multivariate time-series data.

cs.LG

Finite element approximation for a convective Brinkman--Forchheimer problem coupled with a heat equation

We investigate a convective Brinkman--Forchheimer problem coupled with a heat equation. The investigated model considers thermal diffusion and viscosity depending on the temperature. We prove the existence of a solution without restriction on the data and uniqueness when the solution is slightly smoother and the data is suitably restricted. We also propose a finite element discretization scheme for the considered model and derive convergence results and a priori error estimates. Finally, we illustrate the theory with numerical examples.

math.NA

Self-Dimensioning and Planning of Small Cell Capacity in Multitenant 5G Networks

An important concept in the fifth generation of mobile networks is multitenancy, which allows diverse operators sharing the same wireless infrastructure. To support this feature in conjunction with the challenging performance requirements of future networks, more automated and faster planning of the required radio capacity is needed. Likewise, installing small cells is an effective resource to provide greater performance and capacity to both indoor and outdoor places. This paper proposes a new framework for automated cell planning in multitenant small cell networks. In particular, taking advantage of the available network data, a set of detailed planning specifications over time and space domains are generated in order to meet the contracted capacity by each tenant. Then, the network infrastructure and configuration are updated according to an algorithm that considers different actions such as adding/removing channels and adding or relocating small cells. The simulation results show the effectiveness of various methods to derive the planning specifications depending on the correlation between the tenant's and network's traffic demands.

cs.NI

Capacity Self-Planning in Small Cell Multi-Tenant 5G Networks

Multi-tenancy allows diverse agents sharing the infrastructure in the 5 th generation of mobile networks. Such a feature calls for more automated and faster planning procedures in order to adapt the network capacity to the varying traffic demand. To achieve these goals, Small Cells offer network providers more flexible, scalable, and cost-effective solutions compared to macrocell deployments. This paper proposes a novel framework for cell planning in multi-tenant Small Cell networks. In this framework, the tenant's contracted capacity is translated to a set of detailed planning specifications over time and space domains in order to efficiently update the network infrastructure and configuration. Based on this, an algorithm is proposed that considers different actions such as adding/removing channels and adding or relocating small cells. The proposed approach is evaluated considering the deployment of a new tenant, where different sets of planning specifications are tested.

cs.NI

Sharing gNB components in RAN slicing: A perspective from 3GPP/NFV standards

To implement the next Generation NodeBs (gNBs) that are present in every Radio Access Network (RAN) slice subnet, Network Function Virtualization (NFV) enables the deployment of some of the gNB components as Virtual Networks Functions (VNFs). Deploying individual VNF instances for these components could guarantee the customization of each RAN slice subnet. However, due to the multiplicity of VNFs, the required amount of virtual resources will be greater compared to the case where a single VNF instance carries the aggregated traffic of all the RAN slice subnets. Sharing gNB components between RAN slice subnets could optimize the trade-off between customization, isolation and resource utilization. In this article, we shed light on the key aspects in the Third Generation Partnership Project (3GPP)/NFV standards for sharing gNB components. First, we identify four possible scenarios for sharing gNB components. Then, we analyze the impact of sharing on the customization level of each RAN slice subnet. Later, we determine the main factors that enable isolation between RAN slice subnets. Finally, we propose a 3GPP/NFV-based description model to define the lifecycle management of shared gNB components

cs.NI

The Creation Phase in Network Slicing: From a Service Order to an Operative Network Slice

Network slicing is considered a key mechanism to serve the multitude of tenants (e.g. vertical industries) targeted by forthcoming 5G systems in a flexible and cost-efficient manner. In this paper, we present a SDN/NFV architecture with multi-tenancy support. This architecture enables a network slice provider to deploy network slice instances for multiple tenants on-the-fly, and simultaneously provision them with isolation guarantees. Following the Network Slice as-a-Service delivery model, a tenant may access a Service Catalog, selecting the slice that best fits its needs and ordering its deployment. This work provides a detailed view on the stages that a network slice provider must follow to deploy the ordered network slice instance, accommodating it into a multi-domain infrastructure, and putting it operative for tenant's consumption. These stages address critical issues identified in the literature, including (i) the mapping from high-level service requirements to network functions and infrastructure requirements, (ii) the admission control, and (iii) the specific information a network slice descriptor should have. With the proposed architecture and the recommended set of stages, network slice providers can deploy (and later operate) slice instances with great agility, flexibility, and full automation.

cs.NI

Dynamic Graph Queries

Graph databases in many applications---semantic web, transport or biological networks among others---are not only large, but also frequently modified. Evaluating graph queries in this dynamic context is a challenging task, as those queries often combine first-order and navigational features. Motivated by recent results on maintaining dynamic reachability, we study the dynamic evaluation of traditional query languages for graphs in the descriptive complexity framework. Our focus is on maintaining regular path queries, and extensions thereof, by first-order formulas. In particular we are interested in path queries defined by non-regular languages and in extended conjunctive regular path queries (which allow to compare labels of paths based on word relations). Further we study the closely related problems of maintaining distances in graphs and reachability in product graphs. In this preliminary study we obtain upper bounds for those problems in restricted settings, such as undirected and acyclic graphs, or under insertions only, and negative results regarding quantifier-free update formulas. In addition we point out interesting directions for further research.

cs.LO