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2021 IEEE 46th Conference on Local Computer Networks (LCN)最新文献

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Delta-State-Based Synchronization of CRDTs in Opportunistic Networks 机会网络中基于delta状态的crdt同步
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/lcn52139.2021.9524978
F. Guidec, Y. Mahéo, Camille Noûs
{"title":"Delta-State-Based Synchronization of CRDTs in Opportunistic Networks","authors":"F. Guidec, Y. Mahéo, Camille Noûs","doi":"10.1109/lcn52139.2021.9524978","DOIUrl":"https://doi.org/10.1109/lcn52139.2021.9524978","url":null,"abstract":"Conflict-Free Replicated Data Types (CRDTs) are distributed data types that support optimistic replication: replicas can be updated locally, and updates propagate asynchronously among replicas, so consistency is eventually obtained. This ability to tolerate asynchronous communication makes them ideal candidates to serve as software building blocks in opportunistic networks (OppNets), that is, mobile networks in which the dissemination of information can only depend on unpredicted transient radio contacts between pairs of nodes. In this paper we investigate the problem of implementing CRDTs in an Opp-Net, and we propose a delta-state-based algorithm to solve this problem. Experimental results confirm that this algorithm ensures the synchronization of CRDT replicas in an OppNet, and that it outperforms a pure state-based synchronization algorithm when dealing with container CRDTs.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123088265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Anchor-oriented Time and Phase-based Concurrent Self-localization using UWB Radios 基于超宽带无线电的面向锚点的时间和相位同步自定位
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/lcn52139.2021.9524990
Nour Smaoui, Milad Heydariaan, O. Gnawali
{"title":"Anchor-oriented Time and Phase-based Concurrent Self-localization using UWB Radios","authors":"Nour Smaoui, Milad Heydariaan, O. Gnawali","doi":"10.1109/lcn52139.2021.9524990","DOIUrl":"https://doi.org/10.1109/lcn52139.2021.9524990","url":null,"abstract":"Positioning plays an important role in many IoT applications. Ultra-wideband (UWB)-based positioning is an alternative to GPS in indoor environments due to its multipath resilience and its accuracy and precision. In the presence of a large number of targets to localize, conventional UWB localization fails to provide a practical location update rate. UWB concurrency in conjunction with self-localization has been used in both time-based and phase-based localization making the targets to localize (tags), a relatively passive device with the sole role of receiving wireless packets and calculating its own location. More recently, phase-based concurrent angle estimation also offloaded the hardware complexity and cost to the anchors instead of the tags. In this work, our anchor-oriented approach combines inter-anchor and intra-anchor concurrency for phase-based localization but also allows time-based localization. Our experimental evaluation on a testbed consisting of Decawave platform shows that our technique is not only practical but also performant.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"2019 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121109237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
MPRdeep: Multi-Objective Joint Optimal Node Positioning and Resource Allocation for FANETs with Deep Reinforcement learning 基于深度强化学习的fanet多目标联合最优节点定位与资源分配
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524972
Qi Wang, Jianmin Liu, Cunzhuang Liu, Jianhui Huang, Chentao He, Yongjun Xu
{"title":"MPRdeep: Multi-Objective Joint Optimal Node Positioning and Resource Allocation for FANETs with Deep Reinforcement learning","authors":"Qi Wang, Jianmin Liu, Cunzhuang Liu, Jianhui Huang, Chentao He, Yongjun Xu","doi":"10.1109/LCN52139.2021.9524972","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524972","url":null,"abstract":"This paper addresses the problem of UAV positioning and resource allocation under dynamic network conditions and under instantaneous communication demands in FANETs. We propose MPRdeep, an adaptive, deep reinforcement learning (DRL) approach considering several QoS requirements concurrently. MPRdeep learns to optimize relay UAVs’ positions and forwarding probabilities to minimize reliability-achieving delay and reliability-achieving energy consumption. The key advantage is that MPRdeep is able to learn and dynamically adjust the node positioning and resource allocation according to ongoing network conditions. The results show that MPRdeep converges fast and has generalization ability that adapts well under dynamic network conditions and dynamic locations of users. Compared with baseline methods, MPRdeep shows superior performance in terms of lower reliability-achieving delay and lower reliability-achieving energy consumption via simulations and experiments.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127189508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks 物联网网络中物理层干扰检测的有效度量
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/lcn52139.2021.9524936
M. Abdollahi, Kousar Malekinasab, Wanqing Tu, M. Bag-Mohammadi
{"title":"An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks","authors":"M. Abdollahi, Kousar Malekinasab, Wanqing Tu, M. Bag-Mohammadi","doi":"10.1109/lcn52139.2021.9524936","DOIUrl":"https://doi.org/10.1109/lcn52139.2021.9524936","url":null,"abstract":"An active jammer could severely degrade the communication quality for wireless networks. Since all wireless nodes openly access the shared media, the harsh effects are exaggerated by retransmission attempts of affected devices. Fast and precise detection of the jammer is of vital importance for heterogeneous wireless environments such as the Internet of things (IoT). It could activate a series of corrective countermeasures to ensure the robust operation of the network. In this paper, we propose a local, straightforward, and numerical metric called the number of jammed slots (NJS), by which we can quickly detect the presence of a jammer and identify the jammed nodes at the software level in broadcast networks. NJS calculation is carried out by a central node which collects the MAC-layer statuses of all wireless nodes in a periodical fashion. Our simulation results indicate that NJS outperforms current detection methods in terms of accuracy and precision.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127546128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Toward Driver Intention Prediction for Intelligent Vehicles: A Deep Learning Approach 智能汽车驾驶员意图预测:一种深度学习方法
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524995
Mozhgan Nasr Azadani, A. Boukerche
{"title":"Toward Driver Intention Prediction for Intelligent Vehicles: A Deep Learning Approach","authors":"Mozhgan Nasr Azadani, A. Boukerche","doi":"10.1109/LCN52139.2021.9524995","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524995","url":null,"abstract":"High-level scene understanding and situational awareness are fundamental for autonomous vehicles before being widely used on public roads in a thoroughly efficient and safe manner. These tasks involve not only perceiving the current surrounding states but also predicting the future behavior of nearby human-driven vehicles. A large amount of vehicular sensing data can be collected using sensors and networking systems in vehicles. Moreover, with the advent of Dedicated Short Range Communication, vehicles can further transfer intention information to surrounding vehicles. However, real-time intention inference of nearby drivers is still challenging. Our primary focus is to present a novel deep learning-based approach to predict drivers driving behavior at unsignalized T-junctions. We use temporal convolutional networks to analyze sequences of trajectory data for a vehicle approaching the T-junction and classify the maneuver seconds before actual maneuver occurrence. The cross-validation results demonstrate the efficiency of the proposed methodology.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123807691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
SecGrid: a Visual System for the Analysis and ML-based Classification of Cyberattack Traffic SecGrid:一个基于ml的网络攻击流量分析与分类的可视化系统
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524932
M. Franco, Jan von der Assen, Luc Boillat, Christian Killer, B. Rodrigues, E. Scheid, L. Granville, B. Stiller
{"title":"SecGrid: a Visual System for the Analysis and ML-based Classification of Cyberattack Traffic","authors":"M. Franco, Jan von der Assen, Luc Boillat, Christian Killer, B. Rodrigues, E. Scheid, L. Granville, B. Stiller","doi":"10.1109/LCN52139.2021.9524932","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524932","url":null,"abstract":"Due to the increasing number of cyberattacks and respective predictions for the upcoming years with even larger numbers of occurrences, companies are becoming aware not only that the digitization of their businesses is essential, but also that the adoption of efficient cybersecurity strategies is crucial. Therefore, approaches for a better understanding and analysis of cybersecurity are essential.Thus, SecGrid, a Machine Learning (ML) empowered platform for analyzing, classification, and visualization of cyberattacks is introduced. SecGrid implements an extensible set of miners to analyze information from network traces to provide insightful visualizations of malicious traffic given and to classify automatically different types of cyberattacks by using supervised ML. Experiments conducted show high overall usability, scalability in terms of the capacity of the platform to extract information from large files, and high performance and accuracy during the classification of cyberattacks.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128594487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Accelerating MPI Communication Using Floating-point Compression on Lossy Interconnection Networks 在有损互连网络中使用浮点压缩加速MPI通信
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524942
Yao Hu, M. Koibuchi
{"title":"Accelerating MPI Communication Using Floating-point Compression on Lossy Interconnection Networks","authors":"Yao Hu, M. Koibuchi","doi":"10.1109/LCN52139.2021.9524942","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524942","url":null,"abstract":"Approximate communication has arisen as a new opportunity for improving the efficiency of communication in parallel computer systems, which can significantly reduce the communication time by transmitting partial or imprecise messages. In this study, we explore application-level approximate communication techniques on lossy high-performance interconnection networks that leave bit flips. Although existing compression techniques do not assume lossy interconnection networks, our approximate-communication challenge is to co-design a lossy floating-point compression algorithm and a critical bit-flip recovery scheme optimized to a given bit error rate (BER) on a target lossy interconnection network. Our objective is to transfer the maximum amount of approximate data over the least amount of compression overhead and bit-flip recovery time. Our scheme is implemented into several representative communication-intensive MPI (Message Passing Interface) applications, and it is shown that our approximate communication scheme effectively speeds up the total execution time without much loss in the quality of the result.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129451720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Maintenance of Structural Hole Spanners in Dynamic Networks 动态网络结构孔扳手的维护
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524948
Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo
{"title":"Maintenance of Structural Hole Spanners in Dynamic Networks","authors":"Diksha Goel, Hong Shen, Hui Tian, Mingyu Guo","doi":"10.1109/LCN52139.2021.9524948","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524948","url":null,"abstract":"Structural Hole (SH) spanners are the set of users who bridge different groups of users and are vital in numerous applications. Despite their importance, existing work for identifying SH spanners focuses only on static networks. However, real-world networks are highly dynamic where the underlying structure of the network evolves continuously. Consequently, we study SH spanner problem for dynamic networks. We propose an efficient solution for updating SH spanners in dynamic networks. Our solution reuses the information obtained during the initial runs of the static algorithm and avoids the recomputations for the nodes unaffected by the updates. Experimental results show that the proposed solution achieves a minimum speedup of 3.24 over recomputation. To the best of our knowledge, this is the first attempt to address the problem of maintaining SH spanners in dynamic networks.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129674161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
X-Sync: Cross-Technology Clock Synchronization Among Off-the-Shelf Wireless IoT Devices X-Sync:现成无线物联网设备之间的跨技术时钟同步
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524940
R. Hofmann, David Grubmair, C. Boano, K. Römer
{"title":"X-Sync: Cross-Technology Clock Synchronization Among Off-the-Shelf Wireless IoT Devices","authors":"R. Hofmann, David Grubmair, C. Boano, K. Römer","doi":"10.1109/LCN52139.2021.9524940","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524940","url":null,"abstract":"Clock synchronization in distributed IoT systems is a necessary feature to allow a coherent data collection and event detection. This task is challenging, as today's IoT systems often consist of heterogeneous wireless devices using incompatible technologies. Because of this, existing solutions often make use of multi-radio gateways, which allow an indirect synchronization across heterogeneous devices, but increase end-to-end delays and suffer from an increased overhead. In this work, we present X-Sync, a novel approach allowing a direct and bidirectional clock synchronization among off-the-shelf wireless IoT devices with incompatible physical layer. X-Sync leverages cross-technology communication to convey timing information among heterogeneous devices and presents novel techniques to compensate for the inaccuracies in reliably detecting the start of a cross-technology frame. We seamlessly integrate X-Sync into the Contiki-NG operating system and evaluate its performance experimentally on off-the-shelf Bluetooth Low Energy and IEEE 802.15.4 devices, showing that X-Sync achieves a μs-level synchronization accuracy.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125666852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Recovering Colliding LoRa Frames from Uncertainties Using LoRa Coding 利用LoRa编码从不确定性中恢复冲突的LoRa帧
2021 IEEE 46th Conference on Local Computer Networks (LCN) Pub Date : 2021-10-01 DOI: 10.1109/LCN52139.2021.9524949
W. Xiao, N. Rachkidy, A. Guitton
{"title":"Recovering Colliding LoRa Frames from Uncertainties Using LoRa Coding","authors":"W. Xiao, N. Rachkidy, A. Guitton","doi":"10.1109/LCN52139.2021.9524949","DOIUrl":"https://doi.org/10.1109/LCN52139.2021.9524949","url":null,"abstract":"LoRa is one of the leading technologies for Low-Power Wide Area Networks and the Internet of Things. Collisions in LoRa might cause retransmissions, which negatively impact the network performance and scalability. Several algorithms have been proposed to decode colliding frames under specific conditions. However, there remain indistinguishable frames due to uncertainties in some or all symbols. In this paper, we propose a general algorithm that significantly improves the recovery capabilities of existing algorithms by leveraging the LoRa coding techniques. Simulation results show that our algorithm can significantly reduce the number of the failed decoding of LoRa frames and improve the performance of the network.","PeriodicalId":222740,"journal":{"name":"2021 IEEE 46th Conference on Local Computer Networks (LCN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130909237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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