Hasil untuk "Cellular telephone services industry. Wireless telephone industry"

Abdikarim Mohamed Ibrahim, Rosdiadee Nordin, Yahya S. M. Khamayseh et al.

The evolution from Industry 4.0 to Industry 5.0 introduces stringent requirements for ultra reliable low latency communication (URLLC) to support human centric, intelligent, and resilient industrial systems. Sixth-generation (6G) wireless networks aim to meet these requirements through sub-millisecond end-to-end delays, microsecond level jitter, and near perfect reliability, enabled by advances such as terahertz (THz) communication, reconfigurable intelligent surfaces (RIS), multi-access edge computing (MEC), and AI driven cross layer optimization. This paper presents a comprehensive review of URLLC solutions for 6G enabled industry 5.0, organized into a structured taxonomy including application domains, key technical enablers, design challenges, and performance enhancements. The survey examines emerging approaches, including digital twin integration, AI/ML based resource orchestration, Network Function Virtualization (NFV) enabled service function chaining, and cross domain networking, while mapping them to critical industrial scenarios such as smart manufacturing, connected healthcare, autonomous mobility, remote control, and next-generation mobile networks. Performance trade-offs between latency, reliability, scalability, and energy efficiency are analyzed in the context of representative state-of-the-art studies. Finally, the paper identifies open challenges and outlines future research directions to realize deterministic, secure, and sustainable URLLC architectures for Industry 5.0.

Vyron Kampourakis, Christos Smiliotopoulos, Vasileios Gkioulos et al.

Traditional air gaps in industrial systems are disappearing as IT technologies permeate the OT domain, accelerating the integration of wireless solutions like Wi-Fi. Next-generation Wi-Fi standards (IEEE 802.11ax/be) meet performance demands for industrial use cases, yet their introduction raises significant security concerns. A critical knowledge gap exists regarding the empirical prevalence and security configuration of Wi-Fi in real-world industrial settings. This work addresses this by mining the global crowdsourced WiGLE database to provide a data-driven understanding. We create the first publicly available dataset of 1,087 high-confidence industrial Wi-Fi networks, examining key attributes such as SSID patterns, encryption methods, vendor types, and global distribution. Our findings reveal a growing adoption of Wi-Fi across industrial sectors but underscore alarming security deficiencies, including the continued use of weak or outdated security configurations that directly expose critical infrastructure. This research serves as a pivotal reference point, offering both a unique dataset and practical insights to guide future investigations into wireless security within industrial environments.

A. R. Pina, Shams El-Adawy, H. J. Lewandowski et al.

Continued growth of the quantum information science and engineering (QISE) industry has resulted in stakeholders spanning education, industry, and government seeking to better understand the workforce needs. This report presents a framework for the categorization of roles in the QISE industry based on 42 interviews of QISE professionals across 23 companies, as well as a description of the method used in the creation of this framework. The data included information on over 80 positions, which we have grouped into 29 roles spanning four primary categories. For each primary category we provide an overview of what unites the roles within a category, a description of relevant subcategories, and definitions of the individual roles. These roles serve as the basis upon which we generate profiles of these roles, which include information about role critical tasks, necessary knowledge and skills, and educational requirements. Our next report will present such profiles for each of the roles presented herein.

Ashley Hourigan, Ridewaan Hanslo

The demand for rapid software delivery in the Information Technology (IT) industry has significantly intensified, emphasising the need for faster software products and service releases with enhanced features to meet customer expectations. Agile methodologies are replacing traditional approaches such as Waterfall, where flexibility, iterative development and adaptation to change are favoured over rigid planning and execution. DevOps, a subsequent evolution from Agile, emphasises collaborative efforts in development and operations teams, focusing on continuous integration and deployment to deliver resilient and high-quality software products and services. This study aims to critically assess both Agile and DevOps practices in the IT industry to identify the feasibility and applicability of Agile methods in DevOps practices. Eleven semi-structured interviews were conducted with Agile and DevOps practitioners in varying capacities across several sectors within the IT industry. Through thematic analysis, 51 unique codes were extracted and synthesised into 19 themes that reported on each phase of the DevOps lifecycle, specifically regarding the integration and implementation of Agile methods into DevOps practices. Based on the findings, a new understanding detailing the interrelationship of Agile methods in DevOps practices was discussed that met the research objectives.

Lizhen Liang, Han Zhuang, James Zou et al.

Artificial intelligence (AI) has seen fast paced development in industry and academia. However, striking recent advances by industry have stunned the field, inviting a fresh perspective on the role of academic research on this progress. Here, we characterize the impact and type of AI produced by both environments over the last 25 years and establish several patterns. We find that articles published by teams consisting exclusively of industry researchers tend to get greater attention, with a higher chance of being highly cited and citation-disruptive, and several times more likely to produce state-of-the-art models. In contrast, we find that exclusively academic teams publish the bulk of AI research and tend to produce higher novelty work, with single papers having several times higher likelihood of being unconventional and atypical. The respective impact-novelty advantages of industry and academia are robust to controls for subfield, team size, seniority, and prestige. We find that academic-industry collaborations produce the most impactful work overall but do not have the novelty level of academic teams. Together, our findings identify the unique and nearly irreplaceable contributions that both academia and industry make toward the progress of AI.

Peter A. V. Gade, Trygve Skjøtskift, Henrik W. Bindner et al.

Energy-intensive industries can adapt to help balance the power grid. By using a real-world case study of a zinc galvanizing process in Denmark, we show how a modest investment in power control of the furnace enables the provision of various ancillary services. We consider two types of services, namely frequency containment reserve (FCR) and manual frequency restoration reserve (mFRR), and numerically conclude that the monetary value of both services is significant, such that the pay-back time of investment is potentially within a year. The FCR service provision is more preferable as its impact on the temperature of the zinc is negligible.

Ashok Urlana, Charaka Vinayak Kumar, Bala Mallikarjunarao Garlapati et al.

Large language models (LLMs) are playing a pivotal role in deploying strategic use cases across a range of organizations, from large pan-continental companies to emerging startups. The issues and challenges involved in the successful utilization of LLMs can vary significantly depending on the size of the organization. It is important to study and discuss these pertinent issues of LLM adaptation with a focus on the scale of the industrial concerns and brainstorm possible solutions and prospective directions. Such a study has not been prominently featured in the current research literature. In this study, we adopt a threefold strategy: first, we conduct a case study with industry practitioners to formulate the key research questions; second, we examine existing industrial publications to address these questions; and finally, we provide a practical guide for industries to utilize LLMs more efficiently. We release the GitHub\footnote{\url{https://github.com/vinayakcse/IndustrialLLMsPapers}} repository with the most recent papers in the field.

Marco Becattini, Davide Borsatti, Armir Bujari et al.

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.

V. Vanitha, S. Esther Florence, A. Alaguraj et al.

A novel wideband bandpass frequency-selective surface functioning at X, Ku, and Ka bands is proposed in this article. The designed FSS has a metallic square loop and a circular ring, and they are printed on both sides of the FR4 substrate. The proposed design FR4-based single-layer FSS is operating from 11.075 GHz to 22.075 GHz with a fractional bandwidth of 66.36%. The parameters of the square loop and circular ring regulate the characteristics of the passband. The optimum dimension of these parameters is obtained with parametric analysis. The proposed structure is measured and fabricated. However, the measured results strongly agree with the simulated results, which authenticate the proposed design performance.

Shubhangi Bhadauria, Klea Plaku, Yash Deshpande et al.

Industry 4.0 has brought to attention the need for a connected, flexible, and autonomous production environment. The New Radio (NR)-sidelink, which was introduced by the third-generation partnership project (3GPP) in Release 16, can be particularly helpful for factories that need to facilitate cooperative and close-range communication. Automated Guided Vehicles (AGVs) are important for material handling and carriage within these environments, and using NR-sidelink communication can further enhance their performance. An efficient resource allocation mechanism is required to ensure reliable communication and avoid interference between AGVs and other wireless systems in the factory using NR-sidelink. This work evaluates the 3GPP standardized resource allocation algorithm for NR-sidelink for a use case of cooperative carrying AGVs. We suggest further improvements that are tailored to the quality of service (QoS) requirements of an indoor factory communication scenario with cooperative AGVs.The use of NR-sidelink communication has the potential to help meet the QoS requirements for different Industry 4.0 use cases. This work can be a foundation for further improvements in NR-sidelink in 3GPP Release 18 and beyond.

Ke Feng, François Baccelli

This work develops a novel approach toward performance guarantees for all links in arbitrarily large wireless networks. It introduces a spatial network calculus, consisting of spatial regulation properties for stationary point processes and the first steps of a calculus for this regulation, which can be seen as an extension to space of the classical network calculus. Specifically, two classes of regulations are defined: one includes ball regulation and shot-noise regulation, which are shown to be equivalent and upper constraint interference; the other one includes void regulation, which lower constraints the signal power. These regulations are defined both in the strong and weak sense: the former requires the regulations to hold everywhere in space, whereas the latter only requires the regulations to hold as observed by a jointly stationary point process. Using this approach, we derive performance guarantees in device-to-device, ad hoc, and cellular networks under proper regulations. We give universal bounds on the SINR for all links, which gives link service guarantees based on information-theoretic achievability. They are combined with classical network calculus to provide end-to-end latency guarantees for all packets in wireless queuing networks. Such guarantees do not exist in networks that are not spatially regulated, e.g., Poisson networks.

Xiangtai Zuo

Technological innovation is one of the most important variables in the evolution of the textile industry system. As the innovation process changes, so does the degree of technological diffusion and the state of competitive equilibrium in the textile industry system, and this leads to fluctuations in the economic growth of the industry system. The fluctuations resulting from the role of innovation are complex, irregular and imperfectly cyclical. The study of the chaos model of the accumulation of innovation in the evolution of the textile industry can help to provide theoretical guidance for technological innovation in the textile industry, and can help to provide suggestions for the interaction between the government and the textile enterprises themselves. It is found that reasonable government regulation parameters contribute to the accelerated accumulation of innovation in the textile industry.

Mohamed Akram SEDDIKI, Sid Ahmed SOUIAH, Tarik GHODBANI et al.

L’établissement du cadastre général en Algérie et la constitution du livre foncier ont été entrepris, dès 1977 et en premier lieu, dans les régions nord du territoire national, en zones rurales comme en zones urbaines, ainsi que dans les agglomérations des régions sud. Ce  projet porte sur un vaste territoire couvrant les zones dites ‘steppiques’ et s’inscrit dans un cadre de recherche de solutions techniques relatives à l’exploitation de l’imagerie du satellite ALSAT2 pour la maintenance des bases de données graphiques du cadastre steppique, cela, par la détermination des capacités informatives que possède cette image en matière d’identification des objets correspondant à une partie ou la totalité des propriétés foncières. Les informations extraites feront partie intégrante d’un Système d’Informations Foncières multi-sources SIF.

Qilin Xiang, Xin Peng, Chuan He et al.

Microservice architecture advocates a number of technologies and practices such as lightweight container, container orchestration, and DevOps, with the promised benefits of faster delivery, improved scalability, and greater autonomy. However, microservice systems implemented in industry vary a lot in terms of adopted practices and achieved benefits, drastically different from what is advocated in the literature. In this article, we conduct an empirical study, including an online survey with 51 responses and 14 interviews for experienced microservice experts to advance our understanding regarding to microservice practices in industry. As a part of our findings, the empirical study clearly revealed three levels of maturity of microservice systems (from basic to advanced): independent development and deployment, high scalability and availability, and service ecosystem, categorized by the fulfilled benefits of microservices. We also identify 11 practical issues that constrain the microservice capabilities of organizations. For each issue, we summarize the practices that have been explored and adopted in industry, along with the remaining challenges. Our study can help practitioners better position their microservice systems and determine what infrastructures and capabilities are worth investing. Our study can also help researchers better understand industrial microservice practices and identify useful research problems.

Kaikai Yang, Sheng Hong, Qi Zhu et al.

In this paper, we consider the joint angle-range estimation in monostatic FDA-MIMO radar. The transmit subarrays are first utilized to expand the range ambiguity, and the maximum likelihood estimation (MLE) algorithm is first proposed to improve the estimation performance. The range ambiguity is a serious problem in monostatic FDA-MIMO radar, which can reduce the detection range of targets. To extend the unambiguous range, we propose to divide the transmitting array into subarrays. Then, within the unambiguous range, the maximum likelihood (ML) algorithm is proposed to estimate the angle and range with high accuracy and high resolution. In the ML algorithm, the joint angle-range estimation problem becomes a high-dimensional search problem; thus, it is computationally expensive. To reduce the computation load, the alternating projection ML (AP-ML) algorithm is proposed by transforming the high-dimensional search into a series of one-dimensional search iteratively. With the proposed AP-ML algorithm, the angle and range are automatically paired. Simulation results show that transmitting subarray can extend the range ambiguity of monostatic FDA-MIMO radar and obtain a lower cramer-rao low bound (CRLB) for range estimation. Moreover, the proposed AP-ML algorithm is superior over the traditional estimation algorithms in terms of the estimation accuracy and resolution.

Steven L. Brunton, J. Nathan Kutz, Krithika Manohar et al.

Data science, and machine learning in particular, is rapidly transforming the scientific and industrial landscapes. The aerospace industry is poised to capitalize on big data and machine learning, which excels at solving the types of multi-objective, constrained optimization problems that arise in aircraft design and manufacturing. Indeed, emerging methods in machine learning may be thought of as data-driven optimization techniques that are ideal for high-dimensional, non-convex, and constrained, multi-objective optimization problems, and that improve with increasing volumes of data. In this review, we will explore the opportunities and challenges of integrating data-driven science and engineering into the aerospace industry. Importantly, we will focus on the critical need for interpretable, generalizeable, explainable, and certifiable machine learning techniques for safety-critical applications. This review will include a retrospective, an assessment of the current state-of-the-art, and a roadmap looking forward. Recent algorithmic and technological trends will be explored in the context of critical challenges in aerospace design, manufacturing, verification, validation, and services. In addition, we will explore this landscape through several case studies in the aerospace industry. This document is the result of close collaboration between UW and Boeing to summarize past efforts and outline future opportunities.

Andrea G. Forte, Wei Wang, L. Veltri et al.

Over the years, the cellular mobile network has evolved from a wireless plain telephone system to a very complex system providing telephone service, Internet connectivity and many interworking capabilities with other networks. Its air interface performance has increased drastically over time, leading to high throughput and low latency. Changes to the core network, however, have been slow and incremental, with increased complexity worsened by the necessity of backwards-compatibility with older-generation systems such as the Global System for Mobile communication (GSM). In this paper, a new virtualized Peer-to-Peer (P2P) core network architecture is presented. The key idea of our approach is that each user is assigned a private virtualized copy of the whole core network. This enables a higher degree of security and novel services that are not possible in today’s architecture. We describe the new architecture, focusing on its main elements, IP addressing, message flows, mobility management, and scalability. Furthermore, we will show some significant advantages this new architecture introduces. Finally, we investigate the performance of our architecture by analyzing voice-call traffic available in a database of a large U.S. cellular network provider.

Lei Xiong, Haiyang Miao, Bo Ai et al.

In order to satisfy the increasing demand for the higher transmission capacity of “smart station”, millimeter wave (mmWave) technology is expected to play a significant role in the high data rate communication system. Based on the ray-tracing simulation technology, this paper would study wireless channel characteristics of the three-dimensional (3D) model of high-speed railway station at the mmWave band. Key parameters such as path loss exponent, shadow fading factor, delay spread, Rician K-factor, angular spread, power angle spectrum, and spatial correlation are extracted and investigated. These channel characteristics are of value for the selection of antenna arrays and even the design of future 5G communication networks in the railway environment.

Songyuan Li, Jiwei Huang, Bo Cheng et al.

The increasing momentum of service-oriented architecture has led to the emergence of divergent delivered services, where service selection is meritedly required to obtain the target service fulfilling the requirements from both users and service providers. Despite many existing works have extensively handled the issue of service selection, it remains an open question in the case where requests from multiple users are performed simultaneously by a certain set of shared candidate services. Meanwhile, there exist some constraints enforced on the context of service selection, e.g. service placement location and contracts between users and service providers. In this paper, we focus on the QoS-aware service selection with constraints from a fairness aspect, with the objective of achieving max-min fairness across multiple service requests sharing candidate service sets. To be more specific, we study the problem of fairly selecting services from shared candidate sets while service providers are self-motivated to offer better services with higher QoS values. We formulate this problem as a lexicographical maximization problem, which is far from trivial to deal with practically due to its inherently multi-objective and discrete nature. A fairness-aware algorithm for concurrent service selection (FASS) is proposed, whose basic idea is to iteratively solve the single-objective subproblems by transforming them into linear programming problems. Experimental results based on real-world datasets also validate the effectiveness and practicality of our proposed approach.

Tiago M. Fernandez-Carames, Paula Fraga-Lamas

Industry 4.0 is a concept devised for improving the way modern factories operate through the use of some of the latest technologies, like the ones used for creating Industrial Internet of Things (IIoT), robotics or Big Data applications. One of such technologies is blockchain, which is able to add trust, security and decentralization to different industrial fields. This article focuses on analyzing the benefits and challenges that arise when using blockchain and smart contracts to develop Industry 4.0 applications. In addition, this paper presents a thorough review on the most relevant blockchain-based applications for Industry 4.0 technologies. Thus, its aim is to provide a detailed guide for future Industry 4.0 developers that allows for determining how blockchain can enhance the next generation of cybersecure industrial applications.