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Field report on experimental comparison of a WiFi mesh network against commercial 5G in an underground disaster environment

Field report on experimental comparison of a WiFi mesh netwo...

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IEEE international symposium on Safety, Security, and Rescue Robotics (SSRR)

作者： Bravo-Arrabal, Juan Alvarez-Merino, C. S. Fernandez-Lozano, J. J. Antonio Gomez-Ruiz, Jose Mandow, Anthony Barco, Raquel Garcia-Cerezo, Alfonso Univ Malaga CEI Andalucia Tech Inst Mechatron Engn & Cyber Phys Syst IMECH UMA Robot & Mechatron Grp Malaga Spain Univ Malaga CEI Andalucia Tech ETS Ingenier Telecomunicac Telecommun Res Inst TELMA Malaga Spain

ISBN: (纸本)9798350381115;9798350381122

Mobile robots in disaster scenarios such as tunnels, mines, or collapsed structures face communication challenges for reliable video streaming to remote control centers. Commercial fifth-generation (5G) networks provide low latency and high bandwidth, especially in urban areas, but ad hoc WiFi networks with static and robotic nodes can provide a solution to attenuation in occluded areas. This paper offers a field experiment report from a search and rescue (SAR) exercise where we tested a WiFi mesh network against commercial 5G in tunnels 184 m long, 6 m wide, and 4 m high. Two operator streamed video to the Internet through a mesh that consisted of two static nodes and two mobile nodes on unmanned ground vehicles (UGV). Latency was measured for both operators for different video resolutions, as well as for a 5G customer-premises equipment (CPE) on-board a scout-UGV. The paper discusses experimental results and lessons learned.

关键词： Disaster Robotics distributed Robot systems Search and Rescue Mesh networks 5G Underground Scenarios

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Steady State Estimation of an Open Loop distributed Network Based on a feed Forward Neural Network 5

Steady State Estimation of an Open Loop Distributed Network ...

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5th international Conference on Control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Pavlov, Ivan Kudryavtsev, Artem Zatsepina, Violetta Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (纸本)9798350309126

Energy efficiency measurement plays an important role in the operation and design phase of a distribution control system. The main objective of any energy adequacy test is to determine the exact location of the steady state for a known load and active and reactive power flows in each branch. In this case, one of the main results of the calculation is the voltage constancy at the nodes. Iterative methods are usually used to calculate power flows in distributed networks. This leads to the fact that high computational speed and reliability of all operations are required. With this in mind, this paper presents a distributed network model based on feedforward artificial neural networks. Its use allows to increase the level of energy consumption in the distribution system. The validity of the model is determined on the example of a real scheme of a 6-10 kV distribution network with an open loop. © 2023 IEEE.

关键词： Iterative methods

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FedHPM: Online Federated Learning via Heterogeneous Prediction Model 22

FedHPM: Online Federated Learning via Heterogeneous Predicti...

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22nd IEEE international symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Zhang, Zhi Zhang, Shiwen Chen, Shuang Liang, Wei Hunan University of Science and Technology College of Computer Science and Technology Xiangtan China Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798331509712

In the era of big data and growing privacy concerns, Federated Learning (FL) has emerged as a promising solution for collaborative model training while preserving user data privacy. However, FL faces challenges such as inconsistent data quality and frequent client dropouts, which hinder its performance. To address these challenges, we propose FedHPM, a novel framework that leverages the predictive capabilities of Long Short-Term Memory (LSTM) networks. FedHPM incorporates an intelligent client selection mechanism that utilizes LSTM-based analysis of historical data to forecast clients' potential data quality and dropout likelihood. This mechanism enables efficient selection of the top best-performing clients for participation in each round of global model training. By mitigating the impact of dropouts and optimizing the composition of participating clients, FedHPM significantly improves both the convergence speed and final performance of the global model. Through extensive empirical evaluations, we demonstrate the superior performance of FedHPM in enhancing FL stability, accelerating the convergence rate, and maintaining model accuracy. The results highlight the effectiveness of our framework in addressing the challenges associated with data quality and dropouts, thereby advancing the field of federated learning. © 2024 IEEE.

关键词： Federated learning

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distributed Deployment of Aerial Base Stations Considering LoS/NLoS Conditions 35

Distributed Deployment of Aerial Base Stations Considering L...

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35th IEEE international symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Furuta, Makitaro Kimura, Tatsuaki Takine, Tetsuya Osaka University Graduate School of Engineering Department of Information and Communications Technology Japan Doshisha University Faculty of Science and Engineering Department of Information Systems Design Japan

ISBN: (纸本)9798350362244

Aerial base stations (ABSs), i.e., unmanned aerial vehicle-mounted base stations, have emerged as an essential technology to expand the coverage and capacity in next-generation wireless networks. Determining the optimal ABS placement that maximizes the communication quality of users is a critical but challenging problem due to complex air-to-ground (A2G) channel characteristics and inter-cell interference. Although various ABS deployment methods have been proposed, existing methods do not consider the actual line-of-sight (LoS) and non-LoS (NLoS) conditions of A2G channels properly, assuming a spatially independent probabilistic LoS model to simplify the problem and analysis. In this study, we propose a distributed ABS deployment method considering the actual LoS/NLoS conditions. We model the ABS deployment space as a 3D grid space in which the LoS/NLoS condition between each grid point is given and formulate the ABS deployment problem as the maximization problem of the expected number of covered users. By applying a potential game to the problem, we develop a distributed ABS deployment algorithm that probabilistically converges to a Nash equilibrium that maximizes the objective function. Furthermore, we demonstrate through simulation that the proposed method can improve the actual communication quality of users. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Achieving Ultra-low Latency for Timeout-less Congestion Control in Data Center networks 22

Achieving Ultra-low Latency for Timeout-less Congestion Cont...

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22nd IEEE international symposium on Parallel and distributed Processing with Applications, ISPA 2024

作者： Zou, Shaojun Jiang, Yi Qu, Jiacheng Zhang, Tao Hu, Yuanzhen Peng, Yujie Hainan University School of Computer Science and Technology Haikou China Changsha University School of Computer Science and Engineering ChangSha China

ISBN: (纸本)9798331509712

Modern data centers are hosting a great number of various applications (e.g. MapReduce and web search) that require a high fan-in data communication, which easily causes serious packet losses and timeouts, substantially degrading the application performance. To address this issue, various host-based and switch-based transport protocols are proposed to eliminate timeout and improve the user experience. Unfortunately, although existing transport protocols can effectively eliminate the timeout, they inevitably result in persistent queueing backlog and degrade the network performance, especially delay-sensitive short flows. To this end, we propose a general scheme with ultra-low latency called UL2 to address the above problem. Concretely, the sender periodically estimates the queueing delay of each packet on the transmission path and senses the degree of congestion based on its measured result. Then the sender timely yet cautiously executes a pausing transmission operation based on measured queueing delay, guaranteeing fast elimination of queue delays and high link utilization. Our evaluation indicates that UL2 can effectively eliminate queue backlog and reduce the queueing delay by more than 90%. Moreover, UL2 enhances the performance of state-of-the-art transport protocols in terms of flow completion times by up to 44.98%. © 2024 IEEE.

关键词： Packet loss

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Reactive Power Optimization in Distribution Network with Renewable distributed Power Sources 4

Reactive Power Optimization in Distribution Network with Ren...

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4th international Conference on Intelligent Power and systems, ICIPS 2024

作者： Zhang, Yufan Pan, Aiqiang Xiong, Xuejun Zhang, Yajun Liu, Hanxiao Li, Liwei Shanghai Municipal Electric Power Company State Grid Shanghai China Shandong University College of Computer Science and Technology Qingdao China

ISBN: (纸本)9798331532765

In order to solve the problems of reactive power optimization in distribution networks which includes the high proportion of distributed new energy power generation, this paper proposes a multi time scale reactive power optimization method. Firstly, on the day-ahead scale, the slow motion control variables were optimized with the objective function of minimizing the expected network loss, and a master-slave classification period decoupling strategy was proposed to transform the dynamic optimization of discrete variables into Static optimization to simplify the optimization process;Secondly, on the 15 minute scale, rolling optimization of reactive power output of new energy is adopted, with the goal of minimizing the system voltage deviations;Finally, in real time, reactive power output of new energy is optimized at any time with the goal of maintaining a constant voltage at the grid connection point within each time window to suppress voltage stability issues caused by various random fluctuations. Finally, the effectiveness and feasibility of the proposed method were verified using the modified IEEE33 node as an example. © 2024 IEEE.

关键词： Power distribution networks

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The Landscape of Digital Platforms for Bottom-Up Collaboration, Creativity, and Innovation Creation 10th

The Landscape of Digital Platforms for Bottom-Up Collaborati...

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10th international Conference on distributed, Ambient and Pervasive Interactions (DAPI) Held as Part of the 24th international Conference on Human-computer Interaction (HCII)

作者： Katmada, Aikaterini Komninos, Nicos Kakderi, Christina Aristotle Univ Thessaloniki Sch Spatial Planning & Dev Thessaloniki Greece Aristotle Univ Thessaloniki URENIO Res Thessaloniki Greece

ISBN: (纸本)9783031054631;9783031054624

The widespread use of digital networks, technologies, and platforms, that allow humans, physical objects, and machines to interact with each other, has significantly affected the structure, components, and knowledge processes of innovation systems that have been transformed into cyber-physical innovation environments. Such environments operate at various scales and spaces, involve a wider set of actors, and demonstrate collective intelligence, exhibiting, thus, higher efficiency and impact than traditional innovation systems. Therefore, it is justified that there is an increasing research interest for understanding digital crowdsourcing platforms and online communities as a channel of collaborative innovation. Despite the attention such systems receive from different disciplines, there is still limited empirical evidence on their structure and coordination, as well as the mechanics that lead to sustained user participation and the generation of inventive and creative ideas, especially in urban planning and civic participation. This paper aims to conduct an overview of key platform attributes and common human-computer interaction patterns, based on an examination of the pertinent literature, as well as an indicative sample of notable platforms which allow large networks of individuals or communities to access, explore, and exchange knowledge and ideas.

关键词： Digital platforms Human-computer interaction Crowdsourcing Planning & urban design Citizen engagement

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Evasion attacks on ML in domains with nonlinear constraints 24

Evasion attacks on ML in domains with nonlinear constraints

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24th IEEE/ACM international symposium on Cluster, Cloud, and Internet Computing (CCGrid)

作者： Krzyszton, Mateusz Bok, Bartosz Zakieta, Pawel Kolodziej, Joanna Res & Acad Comp Network NASK PIB Dept Distributed Syst Warsaw Poland Cracow Univ Technol Dept Comp Sci Krakow Poland

ISBN: (纸本)9798350377521;9798350377514

Cybersecurity efforts aim to protect computer systems, especially complex systems with dynamically changing architectures like mobile computational clouds, from digital attacks. The use of machine learning (ML) models in these systems to analyze and process data, allocate resources or monitor and manage infrastructure is increasingly the field of hackers and the target of sophisticated and increasingly difficult-to-detect attacks. Adversarial machine learning (AML) is a class of techniques and methods that attempt to "fool" classical ML algorithms by using, among others, deceptive data or modifying the parameters of cyber-physical systems (CPS). This paper presents a new generic evasion attack model for generating targeted attacks on the ML binary classifiers in domains with nonlinear constraints. We used GD (Gradient Descent) and Adam (Adaptive Moment Estimation) optimization algorithms as the most important internal components of two variants of our attack model. Such a model was then evaluated in an experimental analysis. The achieved results show that the new generic evasion attack model effectively generates targeted attacks on ML binary classifiers, utilizing GD and Adam optimization algorithms. This model was evaluated through experimental analysis, demonstrating its potential in cybersecurity contexts. Through this approach, the research contributes significantly to the field of adversarial machine learning by presenting a novel method that challenges the robustness of ML models under specific nonlinear constraints.

关键词： nonlinear constraints machine learning evasion attacks optimization

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What Appears Suboptimal May Surprise You: A Fixed-Rate Scheduling Policy for Geo-distributed CoFlows 29

What Appears Suboptimal May Surprise You: A Fixed-Rate Sched...

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29th IEEE international Conference on Parallel and distributed systems, ICPADS 2023

作者： Liu, Haoyu Ding, Feiyan Wang, Yao Xiang, Qiao Shu, Jiwu Du, Haizhou Kong, Linghe Liu, Xue Xiamen University School of Informatics Xiamen China University of Electric Power of Shanghai School of Computer Science and Technology Shanghai China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China McGill University School of Computer Science Montreal Canada

ISBN: (纸本)9798350330717

All existing coflow scheduling algorithms compute dynamic-rate schedules that change the rates of flows during transmission. In this paper, we make a crucial finding: although dynamically adjusting the rates of flows could lead to a better coflow completion time (CCT) in theory, it would introduce additional pressures on the congestion control mechanism in the underlying network, which result in poor CCT in practice. This difference between theoretical CCT and practical CCT is further exacerbated in wide-area networks, where the topology does not provide any bisection guarantee as data center networks do. To this end, we designed a fixed-rate coflow scheduling policy called FSCO. Although in theory, the best fixed-rate schedule is usually suboptimal, it keeps the in-flight traffic relatively steady, reducing the risk of triggering congestion control. The core of FSCO is an efficient scheduling algorithm based on the classic network utilization maximization (NUM) framework. We implement a prototype of FSCO and evaluate its performance extensively using real-world topologies and coflow traces. Experimental results show that the total CCT reduces up to 30% compared to baselines while yielding up to 12× speedups compared to the solver. © 2023 IEEE.

关键词： Coflow Scheduling Dual decomposition Network Utility Maximization

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Blockchain Interoperability for A Reputation-Based Drug Supply Chain Management 6

Blockchain Interoperability for A Reputation-Based Drug Supp...

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6th international Conference on Information systems and computer networks, ISCON 2023

作者： Tanvir, Deluwar Hussen Amin, Ruhul Islam, Ashraful Islam, Mohammad Shamsul Rashid, Muhammed Mamunur Sylhet Engineering College Department of Computer Science and Engineering Sylhet Bangladesh Faridpur Engineering College Department of Computer Science and Engineering Faridpur Bangladesh System Analyst Investment Corporation of Bangladesh Dhaka Bangladesh

ISBN: (纸本)9798350346961

The pharmaceutical drug industry faces considerable challenges in supply chain management, particularly in regard to tracking and tracing medications. Counterfeit drugs pose a significant global threat, and existing supply chain management practices often prove insufficient to prevent adulteration. Blockchain technology offers a potential solution to these issues by establishing a decentralized and distributed ecosystem where stakeholders can foster a trustworthy relationship. To address these limitations, we propose a blockchain-based system for tracking drugs in the supply chain, incorporating a reputation mechanism to ensure transparency and accountability among entities. To mitigate the interoperability challenges between blockchain networks, we implement inter-blockchain communication using the burn-to-claim protocol. Hyperledger Fabric is used as the primary blockchain because it ensures confidentiality between multiple organizations, and Quorum is the other blockchain. Our solution prioritizes trust, traceability, transparency, and accountability to deliver safe, authentic medication to consumers.. © 2023 IEEE.

关键词： Blockchain

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