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Wireless-Aware TSN Engineering: Implications for 5G and Upcoming 6G Networks

IEEE Network 2025年第3期39卷 99-107页

作者： Egger, Simon Durr, Frank Varga, Balazs De Andrade, Marilet Sharma, Gourav Prateek Sachs, Joachim Harmatos, Janos Gross, James University of Stuttgart Institute for Parallel and Distributed Systems Stuttgart70569 Germany Ericsson Research Budapest1117 Hungary Ericsson Research Stockholm16440 Sweden KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm114 28 Sweden Ericsson Research Aachen52134 Germany

The importance of time- and mission-critical applications is increasing as industries and society are advancing in their digitalization. As such applications introduce stringent quality of service (QoS) requirements on the underlying network infrastructure, open standards like time-sensitive networking (TSN) and DetNet are being developed to provide dependable and time-sensitive communication in bridged LAN networks and IP networks, respectively. More recently, the extension to support wireless time-sensitive connectivity has received special interest due to improved network deployment flexibility with mobile devices. These efforts have led to the standardized support of TSN/DetNet in 5G, allowing the 5G system and its mobile devices to be integrated transparently into TSN/DetNet networks while conforming to their user and control plane protocols. Nevertheless, the induced packet delays– and in particular the packet delay variations (PDVs)– of 5G are significantly larger than in their wired counterparts. In this work, we illustrate that established methods to configure TSN/DetNet networks insufficiently address major runtime uncertainties, and that they would consequently result in QoS impairments or scalability issues. We therefore advocate for two systematic approaches to improve traffic shaping in this setting: first, we propose Packet Delay Correction where the PDV is corrected within the 5G system. Second, we introduce "wireless-aware" TSN scheduling to account for the packet delay characteristics of 5G. We demonstrate that wireless-aware TSN scheduling and Packet Delay Correction are complementary in their design and can be combined to provide formal end-to-end reliability guarantees at scale. In addition, being a key aspect to support wireless-aware TSN scheduling in 5G and future 6G networks, we introduce a data-driven framework to predict the packet delay characteristics of the wireless systems over a finite time horizon. Finally, we identify open research

关键词： Quality of service

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Scalable and Low-Cost Remote Lab Platforms: Teaching Industrial Robotics Using Open-Source Tools and Understanding Its Social Implications 16th

Scalable and Low-Cost Remote Lab Platforms: Teaching Indust...

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9789819635214

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Costs

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Proximity-based service discovery for distributed digital twin systems

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Discover Internet of Things 2025年第1期5卷 1-24页

作者： Rothermel, Kurt Herzog, Otthein Zhiqiang, Siegfried Wu Institute Of Parallel and Distributed Systems University of Stuttgart Universitaetsstr. 38 Stuttgart70569 Germany College of Architecture and Urban Planning Tongji University 1239 Siping Road Shanghai200092 China Department of Mathematics and Computer Science University of Bremen Bibliothekstrasse 5 Bremen23884 Germany

Over the past decade, there has been a significant increase in interest in digital twin (DT) technology in a variety of domains. While research on DTs of single assets was initially prevalent, there has been a notable shift towards distributed systems of DTs, which connect to each other to collaborate. Typically, collaboration is enabled by DTs providing services that can be consumed by other DTs. In service-oriented systems, a service is typically identified by type information. However, this is not sufficient in distributed DT systems, where DTs associated with different physical entities may provide the same type of service. Consequently, selecting the appropriate service depends not only on the service type, but also on the associated physical entity. However, requiring DTs to know the mapping of services to their physical environment is not feasible for large dynamic systems. This paper presents a novel proximity-based service discovery method that allows DTs to select services based on service type and their proximity to other objects. That is, service specifications are fully abstracted from the mapping of services to physical objects, relieving DTs from maintaining information about this mapping. Furthermore, service discovery is robust to changes in the physical environment and service population. The proposed service discovery method has been implemented on top of a spatial DBMS. We argue that this implementation is optimal in terms of network utilization and latency, and perform comprehensive evaluations to show the performance of discovery queries as a function of their complexity. © The Author(s) 2025.

关键词： Location based services

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Challenges and Initial Measurements on Communication and Localization for Mountain Bike Safety Applications

Challenges and Initial Measurements on Communication and Loc...

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Annual Conference on Wireless On Demand Network systems and Services (WONS)

作者： Michele Zucchelli Marcus Marx Max Hörmann Frank Kargl Michele Segata Department of Information Engineering and Computer Science University of Trento Italy Institute of Distributed Systems Ulm University Germany

ISBN: (数字)9783903176713

ISBN: (纸本)9798331522025

As of today, research in vulnerable road users (VRUs) applications is mainly focused on safety in urban road scenarios. There is little to be found in the literature with respect to VRUs in mountain areas, where mountain biking and hiking also present risks of collision. Here, it is not yet clear whether existing localization and communication technologies would provide sufficient performance in such harsh environments. In this work, we start answering this question by presenting the results of a measurement campaign which took place in a mountain area in Northern Italy during Summer 2024. With respect to localization, we show that global navigation satellite system (GNSS)-based localization alone often provides unreliable results due to vegetation and terrain. Trilateration with Bluetooth Low Energy (BLE) and beacons mounted at fixed positions performs well in some circumstances and can be used to enhance GNSS, however, we also observed many unclear effects that require further investigations. Concerning communication, the results indicate that both direct short range communications (DSRC) and cellular V2X (C-V2X) works fairly well in most cases, but terrain characteristics might induce packet losses or low signal quality, whereas instabilities in GNSS fixes might also cause C-V2X outages.

关键词： Location awareness Wireless communication Global navigation satellite system Roads Vegetation mapping Packet loss Communications technology Safety Bluetooth Low Energy Network systems

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MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous Real-Time systems

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ACM Transactions on Design Automation of Electronic systems 2025年第3期30卷 1-29页

作者： Ahmadi-Pour, Sallar Saha, Sangeet Mcdonald-Maier, Klaus Drechsler, Rolf Institute of Computer Science University of Bremen Faculty 3 Mathematics and Computer Science Bremen Bremen Germany Robotics and Embedded Systems Research Group University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom Cyber-Physical Systems DFKI Rheinland-Pfalz Kaiserslautern Germany

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today's Real-Time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： FPGA heuristic HW SW co-design integer linear programming real-time scheduling Task graph

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CTXNL: A Software-Hardware Co-designed Solution for Efficient CXL-Based Transaction Processing 25

CTXNL: A Software-Hardware Co-designed Solution for Efficien...

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30th ACM International Conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： Wang, Zhao Chen, Yiqi Li, Cong Guan, Yijin Niu, Dimin Guan, Tianchan Du, Zhaoyang Wei, Xingda Sun, Guangyu School of Integrated Circuits School of Computer Science Peking University Beijing China Peking University School of Integrated Circuits Beijing China Damo Academy Alibaba Group Hupan Lab Hangzhou China Shanghai Jiao Tong University Institute of Parallel and Distributed Systems Seiee Shanghai China School of Integrated Circuits Beijing Advanced Innovation Center for Integrated Circuits Peking University Beijing China

ISBN: (纸本)9798400710797

Transaction processing systems are the crux for modern data-center applications, yet current multi-node systems are slow due to network overheads. This paper advocates for Compute Express Link (CXL) as a network alternative, which enables low-latency and cache-coherent shared memory accesses. However, directly adopting standard CXL primitives leads to performance degradation due to the high cost of maintaining cross-node cache coherence. To address the CXL challenges, this paper introduces CTXNL, a software-hardware co-designed system that implements a novel hybrid coherence primitive tailored to the loosely coherent nature of transactional data. The core innovation of CTXNL is empowering transaction system developers with the ability to selectively achieve data coherence. Our evaluations on OLTP workloads demonstrate that CTXNL enhances performance, outperforming current network-based systems and achieves up to 2.08x greater throughput than vanilla CXL memory sharing architectures across universal transaction processing policies. © 2025 ACM.

关键词： Cache memory

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City models: past, present and future prospects

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Frontiers of Urban and Rural Planning 2025年第1期3卷 1-24页

作者： Ritter, Helge Herzog, Otthein Rothermel, Kurt Cohn, Anthony G. Wu, Zhiqiang Faculty of Technology Bielefeld University Bielefeld Germany College of Architecture and Urban Planning Tongji University Shanghai People’s Republic of China FB 03 University of Bremen Bremen Germany Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart Germany School of Computer Science University of Leeds Leeds UK The Alan Turing Institute London UK

This paper attempts to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes that define a city’s overall characteristics. For the task of urban planning and urban operation, we take the stance that even if the necessary representations of these structures and processes can be achieved, the most important representation of the relevant mindsets of the citizens are, unfortunately, mostly neglected. After a review of major “traditional” urban models of structures behind urban scale, form, and dynamics, we turn to major recent modeling approaches triggered by recent advances in AI that enable multimodal generative models. Some of these models can create representations of geometries, networks and images, and reason flexibly at a human-compatible semantic level. They provide huge amounts of knowledge extracted from huge collections of text and image documents and cover the required rich representation spectrum including geographic knowledge by different knowledge sources, degrees of granularity and scales. We then discuss what these new opportunities mean for coping with the modeling challenges posed by cities, in particular with regard to the role and impact of citizens and their interactions within the city infrastructure. We propose to integrate these possibilities with existing approaches, such as agent-based models, which opens up new modeling spaces including rich citizen models which are able to also represent social interactions. Finally, we put forward some thoughts about a vision of a “social AI in a city ecosystem” that adds relevant citizen models to state-of-the-art structural and process models. This extended city representation will enable urban planners to establish citizen-oriented planning of city infrastructures, to make them into inviting environments that reconcile and foster human culture, city resilience and sustainability.

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Adaptively Aggregating Pyramid Spatial-temporal Feature for Video Person Re-Identification 25

Adaptively Aggregating Pyramid Spatial-temporal Feature for ...

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Proceedings of the 4th International Conference on computer, Artificial Intelligence and Control Engineering

作者： Zhong Han Qianyue Duan Jianfeng An Huanjie Tao Yangzhou Collaborative Innovation Research Institute of Shenyang Aircraft Design and Research Institute Co. Ltd Yangzhou Jiangsu China School of Computer Science Northwestern Polytechnical University Xi' an Shaanxi China School of Computer Science Northwestern Polytechnical University Xi' an Shaanxi China Engineering and Research Center of Embedded Systems Integration (Northwestern Polytechnical University) Ministry of Education Xi' an Shaanxi China

ISBN: (纸本)9798400712647

Video person re-identification (ReID) aims to identify a particular person from the non-overlapping camera views by matching video sequences. It is challenging due to many complex factors, such as similar appearance, occlusion, pose, and viewpoint variation. Pyramid spatial-temporal aggregation (PSTA) is an important method that addresses these challenges. However, PSTA adopts a simple feature addition operation to fuse the hierarchical feature vectors into the video-level representations for video person ReID, which may cause the discriminative information in the feature vectors to be diluted. To solve the above issue, this paper presents an adaptive pyramid spatial-temporal aggregation network (APSNet) to learn more discriminative features. In APSNet, an adaptive feature fusion module (AFFM) is designed to adaptively recalibrate the channel feature responses by explicitly modeling the interdependence between channels. The designed AFFM can enhance the useful features and suppress the interference features during the feature fusion stage, resulting in more discriminative video-level feature representations. Experimental results demonstrate that APSNet has a better performance than PSTA on the MARS dataset, which reaches 86.2% mAP accuracy and 91.2% Rank-1 accuracy. Our APSNet improves the mAP accuracy by 0.4% compared with PSTA.

关键词： Attention Mechanism

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SatCooper: Enhancing Cooperative Inference Analytics for Satellite Service via Multi-exit DNNs

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IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Qiyang Wang, Shangguang Guan, Jinglong Donta, Praveen Kumar Ma, Xiao Prasad, RangaRao Venkatesha Dustdar, Schahram Liu, Xuanzhe Peking University School of Computer Science Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Stockholm University Department of Computer and Systems Sciences Kista16455 Sweden Beiyou Shenzhen Institute Shenzhen China Netherlands TU Wien Distributed System Group Wien1040 Austria UPF Barcelona Spain

As a key technology of intelligent satellite-enabled services in B5G or 6G networks, deploying Deep Neural Networks (DNN) models on satellites has been a notable trend, catering to the daily demand for extensive computing-intensive and latency-sensitive tasks. The computing resources are strategically deployed on satellites where sensor data is generated or collected, facilitating the fine-grained computational inference of DNN-based tasks. However, no prior study has comprehensively explored the crucial inference challenges-e.g., the trade-off between the number of tasks completed and accuracy and partitioning models in multi-exit models-in the resource-constrained space environment. Effective scheduling frameworks cater to various streams of inference tasks are scarce because inference performance may deviate from the ideal situation due to changes in task system status, such as task profiles and network state. To this end, we first formulate a gain-aware in-orbit computing inference problem to strike a proper trade-off between inference latency and the number of tasks completed by dynamically selecting optimal early exit points and model partitioning points. We propose an offline dynamic programming-based algorithm that provides an effective solution when comprehensive system details are to be predicted. We have developed an online learning-based method to schedule inference tasks with uncertain and dynamic system statuses in real-world situations. Our evaluation shows that, compared to baseline methods, the online learning-based algorithm can improve task gain by an average of 87.3% across various tasks. © 2002-2012 IEEE.

关键词： Dynamic programming

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An Efficient Multi-band Infrared Small Objects Detection Approach for Low-Altitude Artificial Intelligence of Thing

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IEEE Internet of Things Journal 2025年

作者： Peng, Yuhuai Wang, Jing Wang, Wenqian Liu, Lei Atiquzzaman, Mohammed Guizani, Mohsen Dustdar, Schahram Northeastern University School of Computer Science and Engineering Shenyang110819 China Zhiyuan Research Institute Hangzhou310024 China Northeastern University School of Computer Science and Engineering Shenyang110819 China Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China University of Oklahoma School of Computer Science NormanOK73019 United States Mohamed Bin Zayed University of Artificial Intelligence Department of Machine Learning Masdar United Arab Emirates Technische Universität Wien Distributed Systems Group Vienna1040 Austria

As a cutting-edge technology of low-altitude Artificial Intelligence of Thing (AIoT), UAV object detection significantly enhances the surveillance services capabilities of low-altitude AIoT. However, the difficulty of object detection is exacerbated by the high proportion of small and obscure objects in the captured images. To address the mentioned challenges, we present an efficient multi-band infrared small object detection approach for low-altitude intelligent surveillance services. Firstly, we propose the Multi-band infrared Image Fusion algorithm based on Cascade-GAN (MIF-CGAN), which produces fused images with high information entropy and high contrast. Then, the Transformer-based Multi-scale Dense Small Object Detection (MsDSOD) algorithm is proposed. The algorithm consists of the Global-Local Object Detection (G-LOD) network, the Object Dense Area Extraction (O-DAE) module, and the Weighted Boxes Fusion (WBF) module. It extracts small objects features at different scales from infrared images and fuses the global and local detection results to accurately identify small objects in dense scenes. Furthermore, compared to the traditional algorithms, the mean Average Precision (mAP) of MsDSOD is improved by 0.80% and the Average Precision in small object detection (APs) is improved by 0.72%. The proposed algorithm is optimally suited to deal with complex scenes with dense small objects and background occlusion. © 2014 IEEE.

关键词： Infrared imaging

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