2020 IEEE 28th International Conference on Network Protocols (ICNP)最新文献_第2页

Poster: An Experimental Study of Multi-RAT Systems 海报:多鼠系统的实验研究

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259348

Andreas Bäuml, C. Felber, Walter P. Nitzold

引用次数: 0

XFi: Cross-technology IoT Data Collection via Commodity WiFi XFi:通过商品WiFi进行跨技术物联网数据采集

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259363

Ruofeng Liu, Zhimeng Yin, Wenchao Jiang, T. He

{"title":"XFi: Cross-technology IoT Data Collection via Commodity WiFi","authors":"Ruofeng Liu, Zhimeng Yin, Wenchao Jiang, T. He","doi":"10.1109/ICNP49622.2020.9259363","DOIUrl":"https://doi.org/10.1109/ICNP49622.2020.9259363","url":null,"abstract":"Wireless technologies are increasingly diversified to serve various Internet-of-things applications. Yet, our mobile devices (e.g., smartphones) are manufactured with limited types of wireless radio, making it challenging to access the data in the heterogeneous IoT devices. To address this fundamental problem, this work proposes XFi, which enables mobile devices to use commodity WiFi radio to directly and simultaneously collect data from diverse heterogeneous IoT devices. Our critical insight is that when an IoT frame collides with an ongoing WiFi transmission, its IoT data is captured by WiFi receiver and retained even after the demodulation procedures in WiFi hardware. Motivated by this observation, XFi proposes a general approach to obtain IoT data by analyzing the decoded WiFi payload. The method is fully compatible with existing commodity WiFi hardware and generally applicable to various IoT protocols. We implement XFi on commodity devices (e.g., RTL8812au, CC2650, and SX1280). Our comprehensive evaluation demonstrates that XFi can collect data from 8 IoT devices in parallel with over 97% accuracy, offering reliable cross-technology data collection.","PeriodicalId":233856,"journal":{"name":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132250319","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: 14

Invited Paper: Perishable Data in Smart Communities 特邀论文:智慧社区中的易逝数据

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259385

Glenn Ricart

引用次数: 0

Trading off Charging and Sensing for Stochastic Events Monitoring in WRSNs WRSNs随机事件监测中充电与传感的权衡

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259399

Yu Sun, Chi Lin, Haipeng Dai, Qiang Lin, Lei Wang, Guowei Wu

{"title":"Trading off Charging and Sensing for Stochastic Events Monitoring in WRSNs","authors":"Yu Sun, Chi Lin, Haipeng Dai, Qiang Lin, Lei Wang, Guowei Wu","doi":"10.1109/ICNP49622.2020.9259399","DOIUrl":"https://doi.org/10.1109/ICNP49622.2020.9259399","url":null,"abstract":"As an epoch-making technology, wireless power transfer incredibly achieves energy transmission wirelessly, enabling reliable energy supplement for wireless rechargeable sensor networks (WRSNs). Existing methods mainly concentrate on performance improvement theoretically, neglecting the fact that most Commercial Off-The-Shelf (COTS) rechargeable sensors (e.g., WISP and Powercast) are not allowed to conduct sensing and energy harvesting tasks simultaneously, termed charging exclusivity. Therefore, their schemes are not feasible for practical applications. In this paper, we focus on the charging exclusivity issue in stochastic events monitoring while improving network performance. In specific, we pay close attention to trading off charging and sensing tasks and formulate a combinatorial optimization problem with routing constraints. We introduce novel discretization techniques and investigate the routing problem to reformulate the original problem into the maximization of a submodular function. With a slightly relaxed budget, the output of our proposed algorithm is better than (1 1/e)/2 of the optimal solution to the original problem with a −smaller charging radius (1 − ξ)Dc. Through extensive simulations, numerical results show that in terms of charging utility, our algorithm outperforms baseline algorithms by 21.3% on average. Moreover, we conduct test-bed experiments to demonstrate the feasibility of our scheme in real scenarios.","PeriodicalId":233856,"journal":{"name":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","volume":"29 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114001746","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: 22

ICNP 2020 Committees ICNP 2020委员会

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/icnp49622.2020.9259391

引用次数: 0

Optimized Joint Unicast-Multicast Panoramic Video Streaming in Cellular Networks 蜂窝网络中优化的联合单播-多播全景视频流

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259362

Akbar Majidi, A. Zahran

引用次数: 3

RACK for SCTP SCTP机架

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259402

Felix Weinrank, M. Tüxen, E. Rathgeb

引用次数: 1

Legilimens: An Agile Transport for Background Traffic in Cellular Networks 摄神:蜂窝网络中后台流量的敏捷传输

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259406

M. Chaudhry, S. Mathew, Shanyu Zhou, V. Gopalakrishnan, Emir Halepovic, H. Seferoglu, Balajee Vamanan

{"title":"Legilimens: An Agile Transport for Background Traffic in Cellular Networks","authors":"M. Chaudhry, S. Mathew, Shanyu Zhou, V. Gopalakrishnan, Emir Halepovic, H. Seferoglu, Balajee Vamanan","doi":"10.1109/ICNP49622.2020.9259406","DOIUrl":"https://doi.org/10.1109/ICNP49622.2020.9259406","url":null,"abstract":"Large data transfers can result in significant congestion and performance degradation for interactive end-user applications such as web browsing and streaming. While there are existing TCP congestion control algorithms for delivery of large volume data (e.g., LEDBAT, TCP-LP), our results show that these protocols are not effective in cellular networks due to variability in radio channel conditions and the use of cellular schedulers in base stations. We propose Legilimens, an agile TCP variant for cellular downlink transfers, which not only retains desirable properties of existing approaches, but also exploits the properties of the cellular schedulers to estimate load and capacity and addresses the challenges in cellular networks. As a result, Legilimens is able to deliver traffic using only the spare capacity on the downlink. We conduct extensive evaluations of Legilimens in multiple settings—in a large cellular network for real-world performance, on the PhantomNet emulator for controlled experiments, and ns-3 simulator for scaled experiments—all of which demonstrate that Legilimens is superior to existing protocols in transferring large volumes of data without interfering with regular user traffic. Compared to existing low-priority protocols, Legilimens improves the throughput of background flows by 2x on average (up to 5x) without degrading the performance of foreground flows across all the three testbeds.","PeriodicalId":233856,"journal":{"name":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128209371","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

A Blind CSI Prediction Method Based on Deep Learning for V2I Millimeter-Wave Channel 基于深度学习的V2I毫米波信道CSI盲预测方法

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259409

Jingxiang Yang, Liyan Li, Minjian Zhao

{"title":"A Blind CSI Prediction Method Based on Deep Learning for V2I Millimeter-Wave Channel","authors":"Jingxiang Yang, Liyan Li, Minjian Zhao","doi":"10.1109/ICNP49622.2020.9259409","DOIUrl":"https://doi.org/10.1109/ICNP49622.2020.9259409","url":null,"abstract":"With the development of the Internet of vehicles and 5G, there emerge more and more challenging application scenarios with fast time-varying channels and high mobility nodes, such as high speed trains environment and vehicle-to-infrastructure (V2I) communication in highway. To support the reliable vehicular communication and mobile edge computing (MEC), it is important to obtain the future channel state information (CSI), which can help optimize system transmission scheme. In this paper, we propose an efficient blind CSI prediction model, called BCPMN. We first reshape the sampled signal into a specific 2-dimensional matrix. Then we propose a learning framework contains of convolutional neural network (CNN), long short-term memory (LSTM) network and fully connected layers. To validate the proposed model, we conduct extensive experiment in three modulation modes. The results show that the BCPMN achieves highly accurate signal-to-noise ratio (SNR) prediction in the fast changing channel model with different modulation modes. In particular, the proposed model can obtain better performance than other methods, and can achieve better performance than other methods without the payload cost of pilot.","PeriodicalId":233856,"journal":{"name":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133501828","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

Poster: Feasibility of Malware Traffic Analysis through TLS-Encrypted Flow Visualization 海报:通过tls加密流可视化进行恶意软件流量分析的可行性

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI: 10.1109/ICNP49622.2020.9259387

Dongeon Kim, Jihun Han, Jinwoo Lee, Heejun Roh, Wonjun Lee

引用次数: 6