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检索条件"任意字段=IEEE Conference on Local Computer Networks"

共 18609 条记录，以下是11-20 订阅

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Sea Trial Measurements of LTE and HF Performance for Underwater Network Extension 49

Sea Trial Measurements of LTE and HF Performance for Underwa...

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49th conference on local computer networks

作者： Schneider, Gunnar Goetz, Michael Nissen, Ivor Fraunhofer Inst Commun Informat Proc & Ergon FKIE Bonn Germany Bundeswehr Tech Ctr Ships & Naval Weap Maritime T Kiel Germany

ISBN: (纸本)9798350388015;9798350388008

This paper presents an analysis of data collected during sea trials, showcasing the capabilities of the buoy concept outlined in prior publication. Underwater networks that are extended through a wireless network domain can enhance an underwater network's characteristics in terms of bandwidth, robustness, interoperability and distance. Central to the setup is a gateway buoy facilitating connectivity between the underwater network and the surface wireless network. Two distinct sets of measurements were conducted: one utilizing High Frequency (HF) and the other employing Long-Term Evolution (LTE) technology. The primary focus of these measurements is to assess the achievable range. The performance of these wireless technologies plays a crucial role in this analysis.

关键词： IoT underwater networks acoustic communication radio communication gateway buoy routing LTE

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WoFS: A Write-only File System for Privacy-aware Wireless Sensor networks 49

WoFS: A Write-only File System for Privacy-aware Wireless Se...

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49th conference on local computer networks

作者： Jahn, Philipp Sommer, Markus Sterz, Artur Hoechsty, Jonas Freisleben, Bernd Univ Marburg Dept Math Comp Sci Marburg Germany tRackIT Syst GmbH Colbe Germany

ISBN: (纸本)9798350388015;9798350388008

Wireless sensor networks (WSNs) can automate data sensing tasks. To ensure redundancy and manage network connectivity issues, a sensing node stores a copy of the gathered data. Since this data may contain sensitive personal or business information, protecting privacy and preventing unauthorized access is crucial. We introduce the Write-only File System (WoFS), a novel encryption system for WSNs that secures data without user interaction, even if a sensor node is stolen. WoFS utilizes either symmetric encryption with volatile keys via a ratchet mechanism or asymmetric encryption. Asymmetric encryption, while slower, allows operation post-reboot, unlike the ratchet-based method. Our experiments show that WoFS achieves write speeds of 200 MB/s or higher, making it suitable for WSN applications. All developed software and artifacts are available under a permissive open-source license.

关键词： Data Protection

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BandSeer: Bandwidth Prediction for Cellular networks 49

BandSeer: Bandwidth Prediction for Cellular Networks

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49th conference on local computer networks

作者： Denizer, Birkan Landsiedel, Olaf Univ Kiel Kiel Germany

ISBN: (纸本)9798350388015;9798350388008

In the context of cellular networks, such as with 5G and upcoming 6G networks, the available bandwidth of a connection is inherently dynamic. Accurate prediction of future bandwidth availability within a link is essential for latency-sensitive and mission-critical applications such as video streaming or remote driving. Bandwidth prediction ensures efficient utilization of a link and thus prevents delays. This paper introduces BandSeer, a stacked Bi-LSTM-based approach for bandwidth prediction in LTE and 5G cellular networks. BandSeer captures complex correlations in historical metrics better than prior work and outperforms SotA baselines. It achieves reductions of up to 18.32% in RMSE and 26.87% in MAE on the Berlin V2X dataset, and reductions of up to 12.43% in RMSE and 28.45% in MAE on the Beyond 5G dataset compared to the SotA Informer baseline. Furthermore, we argue that any bandwidth algorithm must be resource efficient to enable for development on various devices. Our evaluations show that BandSeer consumes one order of magnitude fewer resources and needs roughly a quarter to half the inference time of its closest competitor, the Informer model.

关键词： Bandwidth Prediction Efficiency 5G Bi-LSTM

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BATMAN Mesh Networking on ESP32's 802.11 49

BATMAN Mesh Networking on ESP32's 802.11

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49th conference on local computer networks

作者： Rotta, Randolf Schulz, Julius Naumann, Billy Chatharajupalli, Navya Sneha Nolte, Joerg Werner, Matthias BTU Cottbus Senftenberg Chair Distributed Syst Operating Syst Cottbus Germany TU Chemnitz Operating Syst Grp Chemnitz Germany

ISBN: (纸本)9798350388015;9798350388008

Mesh routing protocols are widely used in IoT and sensor networks. In recent years, the ESP32 Wi-Fi/BLE SoC became popular for prototyping IoT applications. However, the existing mesh networks for this platform lack efficient node to node communication, fast route discovery and repair, and energy efficiency. This paper addresses the formation of ieee 802.11 based ad-hoc mesh networks without the delays inflicted by the Station to Access Point association protocol. We implemented the B.A.T.M.A.N. protocol on top of the ESP32 Wi-Fi MAC interface and integrated it into the LwIP network stack. The performance evaluation with respect to UDP/IP and TCP/IP end-to-end throughput shows the general usefulness but also identifies bottlenecks caused by limitations of the existing MAC interface. Overall, this opens an interesting opportunity for research on mesh protocols by providing a simpler platform than full featured Wi-Fi routers;and for wireless IoT applications by providing higher throughput than subGHz and BLE technologies.

关键词： Ad hoc networks Wireless mesh networks

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Securing the Internet of Robotic Things: A Federated Learning Approach 49

Securing the Internet of Robotic Things: A Federated Learnin...

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49th conference on local computer networks

作者： Nkoom, Matilda Commey, Daniel Hounsinou, Sena G. Crosby, Garth V. Texas A&M Univ Multidisciplinary Engn College Stn TX 77840 USA Metro State Univ Comp Sci & Cybersecur St Paul MN USA Texas A&M Univ Engn Technol & Ind Distribut College Stn TX USA

ISBN: (纸本)9798350388015;9798350388008

This paper addresses the challenge of Distributed Denial of Service (DDoS) attacks in the Internet of Robotic Things (IoRT) using a federated learning approach. We investigate the performance of Convolutional Neural networks (CNNs), Long Short-Term Memory (LSTM) networks, and Gated Recurrent Units (GRUs) for DDoS detection in IoRT systems. Our models are evaluated using the CICDDoS2019 dataset. The CNN-based model achieves the highest performance with an accuracy of 0.9810 and an F1-score of 0.9800, outperforming LSTM and GRU-based models. We analyze the models' convergence properties and discuss their suitability for resource-constrained IoRT devices. Our results demonstrate the potential of federated learning for enhancing IoRT security while highlighting the trade-offs between model performance and efficiency.

关键词： Federated Learning Internet of Robotic Things(IoRT) Distributed Denial of Service (DDoS) Feed-Forward Neural networks Privacy-preserving intrusion detection Cyber-Physical Systems(CPSs) CICDDoS2019

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Can LLMs Understand computer networks? Towards a Virtual System Administrator 49

Can LLMs Understand Computer Networks? Towards a Virtual Sys...

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49th conference on local computer networks

作者： Donadel, Denis Marchiori, Francesco Pajola, Luca Conti, Mauro Univ Padua Dept Math Padua Italy Spritz Matter Srl Padua Italy Delft Univ Technol Fac Elect Engn Math & Comp Sci Delft Netherlands

ISBN: (纸本)9798350388015;9798350388008

Recent advancements in Artificial Intelligence, and particularly Large Language Models (LLMs), offer promising prospects for aiding system administrators in managing the complexity of modern networks. However, despite this potential, a significant gap exists in the literature regarding the extent to which LLMs can understand computer networks. Without empirical evidence, system administrators might rely on these models without assurance of their efficacy in performing network-related tasks accurately. In this paper, we are the first to conduct an exhaustive study on LLMs' comprehension of computer networks. We formulate several research questions to determine whether LLMs can provide correct answers when supplied with a network topology and questions on it. To assess them, we developed a thorough framework for evaluating LLMs' capabilities in various network-related tasks. We evaluate our framework on multiple computer networks employing proprietary (e.g., GPT4) and open-source (e.g., Llama2) models. Our findings in general purpose LLMs using a zero-shot scenario demonstrate promising results, with the best model achieving an average accuracy of 79.3%. Proprietary LLMs achieve noteworthy results in small and medium networks, while challenges persist in comprehending complex network topologies, particularly for open-source models. Moreover, we provide insight into how prompt engineering can enhance the accuracy of some tasks.

关键词： Large Language Models computer networks System Administrators

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Passive Identification of WiFi Devices At-Scale: A Data-Driven Approach 49

Passive Identification of WiFi Devices At-Scale: A Data-Driv...

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49th conference on local computer networks

作者： Bogahawatta, Niruth Karunanayaka, Yasiru Senarath Seneviratne, Suranga Thilakarathna, Kanchana Masood, Rahat Kanhere, Salil Seneviratne, Aruna Univ Sydney Sydney NSW Australia Univ New South Wales Sydney NSW Australia

ISBN: (纸本)9798350388015;9798350388008

WiFi has emerged as the standard method for local connectivity across various devices, including smart assistants, IoT devices, smart TVs, and AR/VR devices. Identifying WiFi devices in neighborhoods has implications for law enforcement, urban planning, and socio-economic analysis. This paper introduces a novel approach to constructing WiFi device-type signatures using Information Element attributes from wildcard WiFi probe requests. Our method accurately identifies device types even when dealing with randomized MAC addresses and requires minimal training data, thus addressing limitations of existing machine learning and deep learning approaches. We evaluate our approach using a dataset of 51,726 probe requests across 50 device types, achieving an average F1 score of 99%, precision of 99%, and recall of 98% in device-type identification. Importantly, our method outperforms deep learning methods with significantly less training data, achieving a 92% F1 score with only one training sample per device type.

关键词： WiFi Device Identification WLAN Wireless networks

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Optimal Caching Strategy for Data Freshness in IoT Applications with Edge Computing 49

Optimal Caching Strategy for Data Freshness in IoT Applicati...

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49th conference on local computer networks

作者： Sharma, Surabhi Chaudhary, Ajay Peddoju, Sateesh K. Indian Inst Technol Roorkee Dept Comp Sci & Engn Roorkee Uttar Pradesh India

ISBN: (纸本)9798350388015;9798350388008

The monitoring of ambient environments relies heavily on data fetched from sensors in the Internet of Things (IoT) services. However, with the increasing number of mobile users and IoT applications, there has been a surge in traffic on IoT networks, leading to faster draining of sensor batteries. Hence, caching at the IoT Edge has emerged as a promising solution, reducing network congestion and energy consumption. This paper proposes an optimal custom caching strategy tailored to Edge computing. By considering factors such as the number of requests, battery level, and Age of Information (AoI) for each sensor, the Edge node decides whether to command a sensor to send a status update or retrieve data from the cache. We formulate the dynamic content caching challenge as a Markov Decision Process (MDP) to optimize jointly long-term caching costs. The proposed relative value iteration algorithm effectively solves the MDP problem without prior knowledge of user preference. Simulation demonstrates that the proposed policy outperforms the greedy and LRU policies with 10.61% and 44.05% lower cache miss rates, respectively, and a 69% slower energy depletion rate and significantly longer node longevity.

关键词： Internet of Things Edge networks Age of Information Optimal Caching Policy

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Enhancing Geographic Greedy Routing in Sparse LDACS Air-to-Air networks through k-Hop Neighborhood Exploitation 49

Enhancing Geographic Greedy Routing in Sparse LDACS Air-to-A...

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49th conference on local computer networks

作者： Ahmed, Musab Fuger, Konrad Kuladinithi, Koojana Timm-Giel, Andreas Hamburg Univ Technol Inst Commun Networks Hamburg Germany

ISBN: (纸本)9798350388015;9798350388008

The emergence of the L-band Digital Aeronautical Communications System (LDACS) presents a significant opportunity for enabling Air-to-Air (A2A) communication to accommodate the growing number of aircraft. However, it requires overcoming significant Medium Access Control (MAC) delays and enhancing connectivity in sparse networks. Geographic greedy routing, commonly used in Aeronautical Ad-hoc networks, utilizes position information to eliminate the need for topology discovery. Yet, its efficacy declines as network density decreases. With the gradual introduction of aircraft equipped with LDACS, it becomes crucial to improve greedy forwarding performance. This research investigates Greedy-k, a greedy forwarding variant using k-hop neighborhood information, to boost sparse network performance. We introduce a method to minimize beacon size by transmitting a subset of k-hop neighborhood data that fits within an LDACS time slot. We derived the subset size analytically and evaluated the performance through simulations benchmarked against the conventional Greedy-1. Our results indicate that the proposed approach achieves up to 13% higher Packet Delivery Ratio (PDR) than Greedy-1, while capturing additionally 70.1% and 34.6% of 2(nd) and 3(rd) order neighbors, respectively.

关键词： geographic routing greedy forwarding A2A LDACS

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Exploring Effective Sensor Deployment Techniques for Dynamic Region of Interest 49

Exploring Effective Sensor Deployment Techniques for Dynamic...

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49th conference on local computer networks

作者： Amarathunga, Buddhima Sahni, Jyoti Valera, Alvin Victoria Univ Wellington Sch Engn & Comp Sci Wellington New Zealand

ISBN: (纸本)9798350388015;9798350388008

The increasing demand for real-time, adaptive monitoring across various domains, such as environmental surveillance and disaster management, necessitates a shift from static to dynamic sensor deployments within Mobile Wireless Sensor networks (MWSNs). One prominent application scenario involves dynamic changes in the Region of Interest (RoI), requiring sensor redeployment. However, defining dynamic RoI scenarios lacks specificity. To address this gap, this study introduces two distinct categories defining a change in RoI: transformed RoI, where the initial RoI undergoes affine transformations, and evolved RoI, representing entirely new polygonal configurations. Additionally, the study explores limitations within current state-of-the-art distributed deployment algorithms, which hinder performance in dynamic RoI settings. These limitations are investigated through experiments involving two main types of distributed algorithms: geometric-based and virtual force-based deployment algorithms. The findings underscore significant performance challenges faced by existing algorithms in dynamic RoI scenarios, emphasizing the need for the development of more resilient algorithms capable of adapting to dynamic RoIs while ensuring network connectivity and minimizing node movement.

关键词： Mobile Wireless Sensor networks (MWSN) dynamic region of interest dynamic coverage

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