arXiv subjects

Adnan Aijaz

Publications and source records attributed to Adnan Aijaz.

At least 37 records · Page 2Linked to original sources

arXiv2024

Demo: Paving the Way for Smart Manufacturing with 5G/TSN Convergence and Augmented Reality

The fifth-generation (5G) mobile/cellular and time-sensitive networking (TSN) technologies are widely recognized as the key to shaping smart manufacturing for Industry 4.0 and beyond. Converged operation of the two offers end-to-end real-time and deterministic connectivity over hybrid wired and wireless segments. On the other hand, the augmented reality (AR) technology provides various benefits for the manufacturing sector. To this end, this demonstration showcases AR-aided remote assistance use-case over a hybrid TSN and 5G system. The demonstration setup comprises off-the-shelf 5G and TSN devices, a near product-grade 5G system, and an AR solution based on smart glasses. The demonstration shows the viability of over-the air transmission of scheduled TSN traffic and real-time assistance for a local user from a remote environments. Performance results from the demonstration setup are also shown.

cs.NI↗

arXiv2024

5G Replicates TSN: Extending IEEE 802.1CB Capabilities to Integrated 5G/TSN Systems

The IEEE 802.1 time-sensitive networking (TSN) standards improve real-time capabilities of the standard Ethernet. TSN and local/private 5G systems are envisaged to co-exist in industrial environments. The IEEE 802.1CB standard provides fault tolerance to TSN systems via frame replication and elimination for reliability (FRER) capabilities. This paper presents X-FRER, a novel framework for extending FRER capabilities to the 3GPP-defined bridge model for 5G and TSN integration. The different embodiments of X-FRER realize FRER-like functionality through multi-path transmissions in a 5G system based on a single or multiple protocol data unit (PDU) sessions. X-FRER also provides enhanced replication and elimination functionality for integrated deployments. Performance evaluation shows that X-FRER empowers a vanilla 5G system with TSN-like capabilities for end-to-end reliability in integrated TSN and 5G deployments.

cs.NI↗

arXiv2024

Adapting MLOps for Diverse In-Network Intelligence in 6G Era: Challenges and Solutions

Seamless integration of artificial intelligence (AI) and machine learning (ML) techniques with wireless systems is a crucial step for 6G AInization. However, such integration faces challenges in terms of model functionality and lifecycle management. ML operations (MLOps) offer a systematic approach to tackle these challenges. Existing approaches toward implementing MLOps in a centralized platform often overlook the challenges posed by diverse learning paradigms and network heterogeneity. This article provides a new approach to MLOps targeting the intricacies of future wireless networks. Considering unique aspects of the future radio access network (RAN), we formulate three operational pipelines, namely reinforcement learning operations (RLOps), federated learning operations (FedOps), and generative AI operations (GenOps). These pipelines form the foundation for seamlessly integrating various learning/inference capabilities into networks. We outline the specific challenges and proposed solutions for each operation, facilitating large-scale deployment of AI-Native 6G networks.

cs.NI↗

arXiv2024

Time-Sensitive Networking over 5G: Experimental Evaluation of a Hybrid 5G and TSN System with IEEE 802.1Qbv Traffic

Underpinned by the IEEE 802.1 standards, Time-sensitive networking (TSN) empowers standard Ethernet to handle stringent real-time requirements of industrial networking. TSN and private 5G will co-exist in industrial systems; hence, converged operation of the two is crucial to achieving end-to-end deterministic performance. This work conducts a testbed-based evaluation of a hybrid 5G and TSN system with over-the-air transmission of scheduled real-time TSN traffic (based on IEEE 802.1Qbv standard). The main objective is to bring the dynamics of hybrid 5G and TSN deployments to spotlight. The testbed comprises off-the-shelf TSN and 5G devices and a near product-grade 5G system. The results show the impact of 802.1Qbv parameters and 5G system capabilities on end-to-end deterministic performance. The findings of this study have significance for design and optimization of 3GPP-defined bridge model (black box model) for 5G/TSN integration.

cs.NI↗

arXiv2024

Vehicle-to-Grid Technology meets Packetized Energy Management: A Co-Simulation Study

The global energy landscape is experiencing a significant transformation driven by increased awareness of climate change and rapid technological advancements in renewable energy and electric vehicles (EVs). Packetized energy management (PEM) schemes are gaining attention as a potential solution for power management for effective load control. This study presents the development of a co-simulation platform to investigate integration of vehicle-to-grid (V2G) with packetized energy trading (PET) in microgrid scenarios. The platform facilitates the interaction between EVs and prosumers, with a focus on responsive loads, and solar photovoltaic (PV) as intermittently available resources. Using the developed co-simulation, this study evaluates how V2G-capable EVs can enhance the stability and efficiency of PET-based microgrids. The results demonstrate the capability of V2G EVs to act as an energy reservoir, effectively managing demand-side load, thus mitigating its fluctuation from available supply while maintaining quality-of-service.

cs.NI↗

arXiv2024

Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach

Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requirements on future 6G mobile network architectures. To meet these demands, it is essential to transcend classical boundaries and integrate communication, computation, control, and intelligence. This paper presents the 6G-GOALS approach to goal-oriented and semantic communications for AI-Native 6G Networks. The proposed approach incorporates semantic, pragmatic, and goal-oriented communication into AI-native technologies, aiming to facilitate information exchange between intelligent agents in a more relevant, effective, and timely manner, thereby optimizing bandwidth, latency, energy, and electromagnetic field (EMF) radiation. The focus is on distilling data to its most relevant form and terse representation, aligning with the source's intent or the destination's objectives and context, or serving a specific goal. 6G-GOALS builds on three fundamental pillars: i) AI-enhanced semantic data representation, sensing, compression, and communication, ii) foundational AI reasoning and causal semantic data representation, contextual relevance, and value for goal-oriented effectiveness, and iii) sustainability enabled by more efficient wireless services. Finally, we illustrate two proof-of-concepts implementing semantic, goal-oriented, and pragmatic communication principles in near-future use cases. Our study covers the project's vision, methodologies, and potential impact.

eess.SP↗

arXiv2024

UMBRELLA: A One-stop Shop Bridging the Gap from Lab to Real-World IoT Experimentation

UMBRELLA is an open, large-scale IoT ecosystem deployed across South Gloucestershire, UK. It is intended to accelerate innovation across multiple technology domains. UMBRELLA is built to bridge the gap between existing specialised testbeds and address holistically real-world technological challenges in a System-of-Systems (SoS) fashion. UMBRELLA provides open access to real-world devices and infrastructure, enabling researchers and the industry to evaluate solutions for Smart Cities, Robotics, Wireless Communications, Edge Intelligence, and more. Key features include over 200 multi-sensor nodes installed on public infrastructure, a robotics arena with 20 mobile robots, a 5G network-in-a-box solution, and a unified backend platform for management, control and secure user access. The heterogeneity of hardware components, including diverse sensors, communication interfaces, and GPU-enabled edge devices, coupled with tools like digital twins, allows for comprehensive experimentation and benchmarking of innovative solutions not viable in lab environments. This paper provides a comprehensive overview of UMBRELLA's multi-domain architecture and capabilities, making it an ideal playground for Internet of Things (IoT) and Industrial IoT (IIoT) innovation. It discusses the challenges in designing, developing and operating UMBRELLA as an open, sustainable testbed and shares lessons learned to guide similar future initiatives. With its unique openness, heterogeneity, realism and tools, UMBRELLA aims to continue accelerating cutting-edge technology research, development and translation into real-world progress.

cs.NI↗

arXiv2024

NetMind: Adaptive RAN Baseband Function Placement by GCN Encoding and Maze-solving DRL

The disaggregated and hierarchical architecture of advanced RAN presents significant challenges in efficiently placing baseband functions and user plane functions in conjunction with Multi-Access Edge Computing (MEC) to accommodate diverse 5G services. Therefore, this paper proposes a novel approach NetMind, which leverages Deep Reinforcement Learning (DRL) to determine the function placement strategies in RANs with diverse topologies, aiming at minimizing power consumption. NetMind formulates the function placement problem as a maze-solving task, enabling a Markov Decision Process with standardized action space scales across different networks. Additionally, a Graph Convolutional Network (GCN) based encoding mechanism is introduced, allowing features from different networks to be aggregated into a single RL agent. That facilitates the RL agent's generalization capability and minimizes the negative impact of retraining on power consumption. In an example with three sub-networks, NetMind achieves comparable performance to traditional methods that require a dedicated DRL agent for each network, resulting in a 70% reduction in training costs. Furthermore, it demonstrates a substantial 32.76% improvement in power savings and a 41.67% increase in service stability compared to benchmarks from the existing literature.

cs.NI↗

arXiv2023

Efficient and Secure Energy Trading with Electric Vehicles and Distributed Ledger Technology

Efficient energy management of Distributed Renewable Energy Resources (DRER) enables a more sustainable and efficient energy ecosystem. Therefore, we propose a holistic Energy Management System (EMS), utilising the computational and energy storage capabilities of nearby Electric Vehicles (EVs), providing a low-latency and efficient management platform for DRER. Through leveraging the inherent, immutable features of Distributed Ledger Technology (DLT) and smart contracts, we create a secure management environment, facilitating interactions between multiple EVs and energy resources. Using a privacy-preserving load forecasting method powered by Vehicular Fog Computing (VFC), we integrate the computational resources of the EVs. Using DLT and our forecasting framework, we accommodate efficient management algorithms in a secure and low-latency manner enabling greater utilisation of the energy storage resources. Finally, we assess our proposed EMS in terms of monetary and energy utility metrics, establishing the increased benefits of multiple interacting EVs and load forecasting. Through the proposed system, we have established the potential of our framework to create a more sustainable and efficient energy ecosystem whilst providing measurable benefits to participating agents.

cs.NI↗

arXiv2023

Open RAN meets Semantic Communications: A Synergistic Match for Open, Intelligent, and Knowledge-Driven 6G

Improving sustainability, enhancing spectral and energy efficiency, and bringing in-network intelligence and reasoning are the driving forces for 6G. In this context, semantic communications (SemCom) and open radio access networks (Open RAN) are emerging as focal points of research. SemCom is widely viewed as a disruptive paradigm that creates the possibility of knowledge-driven networks. On the other hand, Open RAN paves the way for open and programmable networks with native intelligence. This paper investigates the synergies between SemCom and Open RAN and introduces the concept of semantic-aware Open RAN. It presents the main architectural components and functionalities along with some of the key applications of semantic-aware Open RAN. It also conducts demonstration and evaluation of a remote WiFi localization built on semantic-aware Open RAN. Finally, it highlights some open challenges for semantic-aware Open RAN.

cs.NI↗

arXiv2023

Open RAN for 5G Supply Chain Diversification: The BEACON-5G Approach and Key Achievements

Open RAN brings multi-vendor diversity and interoperability to mobile/cellular networks. It is becoming part of governmental strategies for diversifying telecoms supply chains. This paper describes the approach and key achievements of the BEACON-5G project, jointly funded by the UK government and industry. The BEACON-5G project aims at developing a competitive edge for 5G Open RAN and contributing toward its maturity. It addresses some of the key challenges in this respect and provides various innovations for system integration, network slicing, marketplace integration, cyber security, and white-box RAN. It also conducts real-world technology trials for urban use-cases. The paper also captures some of the key lessons learned during delivery, the main outcomes, and highlights potential impact on the wider UK 5G diversification strategy.

cs.NI↗

arXiv2023

Demo: A Digital Twin of the 5G Radio Access Network for Anomaly Detection Functionality

Recently, the concept of digital twins (DTs) has received significant attention within the realm of 5G/6G. This demonstration shows an innovative DT design and implementation framework tailored toward integration within the 5G infrastructure. The proposed DT enables near real-time anomaly detection capability pertaining to user connectivity. It empowers the 5G system to proactively execute decisions for resource control and connection restoration.

cs.NI↗

arXiv2023

Demo: Integration of Marketplace for the 5G Open RAN Ecosystem

The Open RAN API and interface standards facilitate the new ecosystems where distinct hardware and software components are brought together to build 5G systems. Key to this concept is the seamless and efficient integration and monetization process among stakeholders. A marketplace serves as a means to realize this collaborative revenue sharing, eliminating the need for intricate proprietary agreements or contracts between each participant. This demo presents the marketplace strategy emphasizing software integration across diverse deployment settings, utilizing the API-centric integration Platform-as-a-Service (iPaas) model aligned with Open RAN standards.

cs.NI↗

arXiv2023

Distributed Sensing, Computing, Communication, and Control Fabric: A Unified Service-Level Architecture for 6G

With the advent of the multimodal immersive communication system, people can interact with each other using multiple devices for sensing, communication and/or control either onsite or remotely. As a breakthrough concept, a distributed sensing, computing, communications, and control (DS3C) fabric is introduced in this paper for provisioning 6G services in multi-tenant environments in a unified manner. The DS3C fabric can be further enhanced by natively incorporating intelligent algorithms for network automation and managing networking, computing, and sensing resources efficiently to serve vertical use cases with extreme and/or conflicting requirements. As such, the paper proposes a novel end-to-end 6G system architecture with enhanced intelligence spanning across different network, computing, and business domains, identifies vertical use cases and presents an overview of the relevant standardization and pre-standardization landscape.

cs.NI↗

arXiv2022

Toward Multi-Service Edge-Intelligence Paradigm: Temporal-Adaptive Prediction for Time-Critical Control over Wireless

Time-critical control applications typically pose stringent connectivity requirements for communication networks. The imperfections associated with the wireless medium such as packet losses, synchronization errors, and varying delays have a detrimental effect on performance of real-time control, often with safety implications. This paper introduces multi-service edge-intelligence as a new paradigm for realizing time-critical control over wireless. It presents the concept of multi-service edge-intelligence which revolves around tight integration of wireless access, edge-computing and machine learning techniques, in order to provide stability guarantees under wireless imperfections. The paper articulates some of the key system design aspects of multi-service edge-intelligence. It also presents a temporal-adaptive prediction technique to cope with dynamically changing wireless environments. It provides performance results in a robotic teleoperation scenario. Finally, it discusses some open research and design challenges for multi-service edge-intelligence.

cs.NI↗

arXiv2022

Haptic Teleoperation goes Wireless: Evaluation and Benchmarking of a High-Performance Low-Power Wireless Control Technology

Communication delays and packet losses are commonly investigated issues in the area of robotic teleoperation. This paper investigates application of a novel low-power wireless control technology (GALLOP) in a haptic teleoperation scenario developed to aid in nuclear decommissioning. The new wireless control protocol, which is based on an off-the-shelf Bluetooth chipset, is compared against standard implementations of wired and wireless TCP/IP data transport. Results, through objective and subjective data, show that GALLOP can be a reasonable substitute for a wired TCP/IP connection, and performs better than a standard wireless TCP/IP method based on Wi-Fi connectivity.

cs.NI↗

arXiv2022

Peer-to-Peer Energy Trading meets IOTA: Toward a Scalable, Low-Cost, and Efficient Trading System

Peer-to-Peer (P2P) energy trading provides various benefits over conventional wholesale energy markets and makes renewable energy more accessible. This paper proposes a novel multi-layer P2P energy trading system for microgrids based on IOTA 2.0, which is a distributed ledger technology (DLT) primarily designed for Internet-of-Things (IoT) applications. The proposed energy trading system, which is a manifestation of a cyber-physical system (CPS), exploits the benefits brought by IOTA's unique ledger structure as well as the recently introduced IOTA smart contract protocol (ISCP). Further, it implements a uniform double-auction market mechanism and a hierarchical routing structure for interconnected microgrids. Performance evaluation demonstrates key benefits over wholesale markets as well as speed, energy efficiency and cost benefits over conventional blockchain-based P2P energy trading systems.

cs.NI↗

arXiv2022

IOTA Tangle 2.0: Toward a Scalable, Decentralized, Smart, and Autonomous IoT Ecosystem

IOTA Tangle is a distributed ledger technology (DLT), primarily designed for Internet-of-Things (IoT) networks and applications. IOTA Tangle utilizes a direct acyclic graph (DAG) structure for the ledger, with its protocol offering features attractive to the IoT domain, over most blockchain alternatives, such as feeless transactions, higher achievable transactions per second (TPS), and lower energy consumption. The original IOTA implementation relied on a bootstrap centralized coordinator solution for consensus which limited its degree of decentralization and scalability. This concern, alongside other limitations to its adoption, such as lack of smart contracts, are being addressed with the release of IOTA 2.0. This update brings with it significant changes in order to remove the coordinator and achieve a scalable decentralized solution. To this end, this paper provides a technical overview of the key features of IOTA 2.0 while discussing their relevance and benefits for the wider IoT ecosystem. The paper also provides performance insights and future research directions for IOTA 2.0.

cs.NI↗