2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)最新文献

Benchmarking Performance of Ethereum Blockchain on Resource Constrained Devices 以太坊区块链在资源受限设备上的性能基准测试

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00009

Suhail Al Marzouqi, Michael Baddeley, Martin Andreoni Lopez

{"title":"Benchmarking Performance of Ethereum Blockchain on Resource Constrained Devices","authors":"Suhail Al Marzouqi, Michael Baddeley, Martin Andreoni Lopez","doi":"10.1109/cps-iotbench56135.2022.00009","DOIUrl":"https://doi.org/10.1109/cps-iotbench56135.2022.00009","url":null,"abstract":"Blockchain has challenged many of the conventions around digital security. In essence, blockchain supports a decentralized platform maintained by peers instead of a single entity. Furthermore, the data in the blockchain is immutable and is being held in a secure and encrypted way. However, running the blockchain on resource-limited devices, such as a consumer PC or a low-power Raspberry Pi as opposed to dedicated servers, is demanding due to the resource limitation in energy, memory, and time taken to validate the transaction on the blockchain. This paper explores these limitations by evaluating and benchmarking the blockchain framework Geth: a terminal interface for the Ethereum blockchain which makes it possible to create a private blockchain in addition to joining the actual blockchain. This article employs a private blockchain within Geth and benchmarks the blockchain to highlight the differences (and limitations) between the devices. Specifically, we make the following observations: (i) the time it takes to validate and add the transaction to the blockchain on a Raspberry Pi 4 is markedly slower compared to an Intel i9-10885H CPU @ 2.40GHz, (ii) the transaction between PCs compared to transactions between Pis is around two orders of magnitude higher. These valuable insights can be used to help researchers in the design and implementation of blockchain-driven security architectures for distributed systems, such as industrial IoT deployments and UAV swarms.","PeriodicalId":371398,"journal":{"name":"2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128884218","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: 1

Benchmarking Audio-based Deep Learning Models for Detection and Identification of Unmanned Aerial Vehicles 基于音频的无人机检测和识别深度学习模型的基准测试

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00008

Sai Srinadhu Katta, S. Nandyala, E. Viegas, Abdelrahman AlMahmoud

{"title":"Benchmarking Audio-based Deep Learning Models for Detection and Identification of Unmanned Aerial Vehicles","authors":"Sai Srinadhu Katta, S. Nandyala, E. Viegas, Abdelrahman AlMahmoud","doi":"10.1109/cps-iotbench56135.2022.00008","DOIUrl":"https://doi.org/10.1109/cps-iotbench56135.2022.00008","url":null,"abstract":"Over the last few years, Unmanned Aerial Vehicles (UAVs) have become increasingly popular for both commercial and personal applications. As a result, security concerns in both physical and cyber domains have been raised, as a malicious UAV can be used for the jamming of nearby targets or even for carrying explosive assets. UAV detection and identification is a very important task for safety and security. In this regard, several techniques have been proposed for the detection and identification of UAVs, in general, through image, audio, radar, and RF based approaches. In this paper, we benchmark the detection and identification of UAVs via audio data from [1]. We benchmarked with widely used deep learning algorithms such as Deep Neural Networks (DNN), Convolutional Neural Network (CNN), Long Short Term Memory (LSTM), Convolutional Long Short Term Memory (CLSTM) and Transformer Encoders (TE). In addition to the dataset of [1], we collected our own diverse identification audio dataset and experimented with Deep Neural Networks (DNN). In a UAV detection task, our best model (LSTM) outperformed the best model of [1] (CRNN) by over 4% in accuracy, 2% in precision, 4% in recall and 4% in F1-score. In UAV identification task, our best model (LSTM) outperformed the best model of [1] (CNN) by over 5% in accuracy, 2% in precision, 4% in recall and 3% in F1-score.","PeriodicalId":371398,"journal":{"name":"2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114562840","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

On the Performance of IEEE 802.15.4z-Compliant Ultra-Wideband Devices IEEE 802.15.4z超宽带设备性能研究

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00012

Michael Stocker, Hannah Brunner, Maximilian Schuh, C. Boano, K. Römer

引用次数: 6

Regression Model Trees: Compact Energy Models for Complex IoT Devices 回归模型树:用于复杂物联网设备的紧凑能量模型

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/CPS-IoTBench56135.2022.00007

Daniel Friesel, O. Spinczyk

{"title":"Regression Model Trees: Compact Energy Models for Complex IoT Devices","authors":"Daniel Friesel, O. Spinczyk","doi":"10.1109/CPS-IoTBench56135.2022.00007","DOIUrl":"https://doi.org/10.1109/CPS-IoTBench56135.2022.00007","url":null,"abstract":"The energy and timing behaviour of embedded components such as radio chips or sensors plays an important role when developing energy-efficient cyber-physical systems and IoT devices. However, datasheet values generally have low accuracy and may be incomplete, and performing new energy measurements after each code or hardware configuration change is time-consuming. While energy models – automatically generated from benchmarks exercising all relevant device configurations – offer a solution, they should have both low prediction error and low complexity in order to be useful to humans as well as energy simulations. With today’s increasingly complex devices and drivers, generating compact and accurate energy models is becoming harder due to non-linear effects and interdependencies between configuration parameters. To address this issue, we present Regression Model Trees. By combining software product line engineering and energy modeling methodologies, these are capable of automatically learning complex energy models from benchmark data. Using energy and timing benchmarks on two embedded radio chips and an air quality sensor, we show that Regression Model Trees are both more accurate than conventional energy models and less complex than state-of-the-art approaches from the product line engineering community. Thus, they are easier to understand and use for humans and algorithms alike. We observe two-to 100-fold complexity reduction, and a maximum energy model error of 6 % with cross-validation.","PeriodicalId":371398,"journal":{"name":"2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124921691","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

First Steps in Benchmarking the Performance of Heterogeneous Ultra-Wideband Platforms 异构超宽带平台性能基准测试的第一步

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00013

Maximilian Schuh, Hannah Brunner, Michael Stocker, Markus Schuss, C. Boano, K. Römer

{"title":"First Steps in Benchmarking the Performance of Heterogeneous Ultra-Wideband Platforms","authors":"Maximilian Schuh, Hannah Brunner, Michael Stocker, Markus Schuss, C. Boano, K. Römer","doi":"10.1109/cps-iotbench56135.2022.00013","DOIUrl":"https://doi.org/10.1109/cps-iotbench56135.2022.00013","url":null,"abstract":"The recent gain in popularity of ultra-wideband (UWB) technology and the rapid development of new-generation transceivers triggered by the IEEE 802.15.4z amendment has led to a large number of UWB systems being deployed and to an increasingly heterogeneous ecosystem. This growing heterogeneity calls for quantitative performance comparisons across different hardware platforms on a large scale, so to identify their strength and weaknesses and to verify whether heterogeneous devices can interact with each other seamlessly. Additionally, the recent opening of the 6 GHz band has raised major concerns in the UWB community, as Wi-Fi 6E is now allowed to operate in the same unlicensed spectrum used by UWB devices. Therefore, the ability to examine and compare the performance of different UWB platforms in presence of Wi-Fi 6E interference is key to develop robust and dependable solutions. In this paper, we describe our first steps towards the development of a large-scale testbed facility that allows us to benchmark and shed light on the performance of different UWB platforms in the absence and presence of cross-technology interference, as well as on their interoperability. We further present preliminary results comparing the communication performance of old- and new-generation UWB platforms, namely the Decawave DW1000 and Qorvo DW3000, as a function of different physical layer settings and with or without co-located Wi-Fi 6E activity.","PeriodicalId":371398,"journal":{"name":"2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127115563","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: 5

Reproducing Key Results from "Restructuring Endpoint Congestion Control" 再现“重构端点拥塞控制”的关键结果

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00010

Tushar Dhoot, Joe Zhang

{"title":"Reproducing Key Results from \"Restructuring Endpoint Congestion Control\"","authors":"Tushar Dhoot, Joe Zhang","doi":"10.1109/cps-iotbench56135.2022.00010","DOIUrl":"https://doi.org/10.1109/cps-iotbench56135.2022.00010","url":null,"abstract":"This work is a reproduction of Narayan et. al’s paper [8] which introduced the Congestion Control Plane (CCP) as a mechanism to develop congestion control algorithms. CCP can be leveraged to improve TCP/IP for Internet of Things (IoT) networks and is therefore relevant in the conversation around the suitability of TCP/IP for IoT applications as described by Dunkels et. al [4].Our reproduction experiments confirm CCP has high fidelity with congestion control implemented directly in the OS kernel. With one exception, our study also confirms that CCP algorithms do not materially differ in their performance. These results affirm that CCP is a promising enhancement over kernel level congestion control.Our experiments did find areas of concern. We discovered several inoperable artifacts in the code provided by the authors. Our experimental setup surfaced issues with reproducing the original results due to changes in the underlying systems. We discovered a graph that was accidentally mislabeled in a material way. Finally, we found a small subset of performance measurements could not be reproduced and flagged these for further research. We also proposed improvements to how replication environments are shared as a general suggestion to improve reproducibility.","PeriodicalId":371398,"journal":{"name":"2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130189419","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

Signal Loss in Body Coupled Communication: Guide for Accurate Measurements 体耦合通信中的信号损失:精确测量指南

2022 Workshop on Benchmarking Cyber-Physical Systems and Internet of Things (CPS-IoTBench) Pub Date : 2022-05-01 DOI: 10.1109/cps-iotbench56135.2022.00011

Juris Ormanis, Vladislavs Medvedevs, V. Abolins, G. Gaigals, Atis Elsts

引用次数: 2