ACM Transactions on Sensor Networks最新文献_第3页

Exploiting Fine-grained Dimming with Improved LiFi Throughput 利用细粒度调光提高 LiFi 吞吐量

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-02-13 DOI: 10.1145/3643814

Xiao Zhang, James Mariani, Li Xiao, Matt W. Mutka

{"title":"Exploiting Fine-grained Dimming with Improved LiFi Throughput","authors":"Xiao Zhang, James Mariani, Li Xiao, Matt W. Mutka","doi":"10.1145/3643814","DOIUrl":"https://doi.org/10.1145/3643814","url":null,"abstract":"Optical wireless communication (OWC) shows great potential due to its broad spectrum and the exceptional intensity switching speed of LEDs. Under poor conditions, most OWC systems switch from complex and more error prone high-order modulation schemes to more robust On-Off Keying (OOK) modulation defined in the IEEE OWC standard. This paper presents LiFOD, a high-speed indoor OOK-based OWC system with fine-grained dimming support. While ensuring fine-grained dimming, LiFOD remarkably achieves robust communication at up to 400 Kbps at a distance of 6 meters. This is the first time that the data rate has improved via OWC dimming in comparison to the previous approaches that consider trading off dimming and communication. LiFOD makes two key technical contributions. First, LiFOD utilizes Compensation Symbols (CS) as a reliable side-channel to represent bit patterns dynamically and improve throughput. We firstly design greedy-based bit pattern mining. Then we propose 2D feature enhancement via YOLO model for real-time bit pattern mining. Second, LiFOD synchronously redesigns optical symbols and CS relocation schemes for fine-grained dimming and robust decoding. Experiments on low-cost Beaglebone prototypes with commercial LED lamps and the photodiode (PD) demonstrate that LiFOD significantly outperforms the state-of-art system with 2.1x throughput on the SIGCOMM17 data-trace.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"53 29 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139761827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Experimental Study on BLE 5 Mesh Applied to Public Transportation BLE 5 网格应用于公共交通的实验研究

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-02-12 DOI: 10.1145/3647641

Anderson Biegelmeyer, Alexandre dos Santos Roque, Edison Pignaton de Freitas

{"title":"An Experimental Study on BLE 5 Mesh Applied to Public Transportation","authors":"Anderson Biegelmeyer, Alexandre dos Santos Roque, Edison Pignaton de Freitas","doi":"10.1145/3647641","DOIUrl":"https://doi.org/10.1145/3647641","url":null,"abstract":"Nowadays In-Vehicle Wireless Sensor Networks (IVWSN) are taking place in car manufacturers because it saves time in the assembling process, saves costs in harness and after-sales, and represents less weight on vehicles helping in diminishing fuel consumption. There is no definition for wireless solution technology for IVWSN, because each one has its own characteristics, and probably this is one of the reasons for its smooth usage in the automotive industry. A gap identified in Wireless Sensor Networks (WSN) for the automotive domain is that the related literature focuses only on ordinary cars with a star topology and few of them with mesh topology. This paper aims to cover this gap by presenting an experimental study performed on verifying the new Bluetooth 5 technology working in a mesh topology applied to public transportation systems (buses). In order to perform this evaluation, a setup to emulate an IVWSN was deployed in a working city bus. Measuring the network metrics, the bus was placed under work in a variety of conditions during its trajectory to determine the influence of the passengers and the whole environment in the data transmission. The results suggest Bluetooth 5 in a mesh topology as a promising candidate for IVWSN because it showed the robustness of losing only 0.16% packets in the worst test, as well as its ability to cover a wider range compared to its previous version, indeed a better RSSI and jitter, with lower transmission power, compared to a star topology. The round trip time results can supports the analysis for time-critical applications.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"4 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139762020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flow-Time Minimization for Timely Data Stream Processing in UAV-Aided Mobile Edge Computing 无人机辅助移动边缘计算中及时处理数据流的流时最小化

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-02-02 DOI: 10.1145/3643813

Zichuan Xu, Haiyang Qiao, Weifa Liang, Zhou Xu, Qiufen Xia, Pan Zhou, Omer F. Rana, Wenzheng Xu

{"title":"Flow-Time Minimization for Timely Data Stream Processing in UAV-Aided Mobile Edge Computing","authors":"Zichuan Xu, Haiyang Qiao, Weifa Liang, Zhou Xu, Qiufen Xia, Pan Zhou, Omer F. Rana, Wenzheng Xu","doi":"10.1145/3643813","DOIUrl":"https://doi.org/10.1145/3643813","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) has gained increasing attentions by both academic and industrial communities, due to its flexible deployment and efficient line-of-sight communication. Recently, UAVs equipped with base stations have been envisioned as a key technology to provide 5G network services for mobile users. In this paper, we provide timely services on the data streams of mobile users in a UAV-aided Mobile Edge Computing (MEC) network, in which each UAV is equipped with a 5G small-cell base station for communication and data processing. Specifically, we first formulate a flow-time minimization problem by jointly caching services and offloading tasks of mobile users to the UAV-aided MEC with the aim to minimize the flow-time, where the flow-time of a user request is referred to the time duration from the request issuing time point to its completion point, subject to resource and energy capacity on each UAV. We then propose a spatial-temporal learning optimization framework. We also devise an online algorithm with a competitive ratio for the problem based upon the framework, by leveraging the round-robin scheduling and dual fitting techniques. Finally, we evaluate the performance of the proposed algorithms through experimental simulation. The simulation results demonstrated that the proposed algorithms outperform their comparison counterparts, by reducing the flow-time no less than 19% on average.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"2 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139668926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SecEG: A Secure and Efficient Strategy against DDoS Attacks in Mobile Edge Computing SecEG：针对移动边缘计算中 DDoS 攻击的安全高效策略

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-23 DOI: 10.1145/3641106

Haiyang Huang, Tianhui Meng, Jianxiong Guo, Xuekai Wei, Weijia Jia

{"title":"SecEG: A Secure and Efficient Strategy against DDoS Attacks in Mobile Edge Computing","authors":"Haiyang Huang, Tianhui Meng, Jianxiong Guo, Xuekai Wei, Weijia Jia","doi":"10.1145/3641106","DOIUrl":"https://doi.org/10.1145/3641106","url":null,"abstract":"Application-layer distributed denial-of-service (DDoS) attacks incapacitate systems by using up their resources, causing service interruptions, financial losses, and more. Consequently, advanced deep-learning techniques are used to detect and mitigate these attacks in cloud infrastructures. However, in mobile edge computing (MEC), it becomes economically impractical to equip each node with defensive resources, as these resources may largely remain unused in edge devices. Furthermore, current methods are mainly concentrated on improving the accuracy of DDoS attack detection and saving CPU resources, neglecting the effective allocation of computational power for benign tasks under DDoS attacks. To address these issues, this paper introduces SecEG, a secure and efficient strategy against DDoS attacks for MEC that integrates container-based task isolation with lightweight online anomaly detection on edge nodes. More specifically, a new model is proposed to analyze resource contention dynamics between DDoS attacks and benign tasks. Subsequently, by employing periodic packet sampling and real-time attack intensity predicting, an autoencoder-based method is proposed to detect DDoS attacks. We leverage an efficient scheduling method to optimize the edge resource allocation and the service quality for benign users during DDoS attacks. When executed in the real-world edge environment, our experimental findings validate the efficacy of the proposed SecEG strategy. Compared to conventional methods, the service rate of benign requests increases by 23% under intense DDoS attacks, and the CPU resource is saved up to 35%.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"10 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Holistic Energy Awareness and Robustness for Intelligent Drones 智能无人机的整体能源意识和鲁棒性

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-23 DOI: 10.1145/3641855

Ravi Raj Saxena, Joydeep Pal, Srinivasan Iyengar, Bhawana Chhaglani, Anurag Ghosh, Venkata N. Padmanabhan, Prabhakar T. Venkata

{"title":"Holistic Energy Awareness and Robustness for Intelligent Drones","authors":"Ravi Raj Saxena, Joydeep Pal, Srinivasan Iyengar, Bhawana Chhaglani, Anurag Ghosh, Venkata N. Padmanabhan, Prabhakar T. Venkata","doi":"10.1145/3641855","DOIUrl":"https://doi.org/10.1145/3641855","url":null,"abstract":"Drones represent a significant technological shift at the convergence of on-demand cyber-physical systems and edge intelligence. However, realizing their full potential necessitates managing the limited energy resources carefully. Prior work looks at factors such as battery characteristics, intelligent edge sensing considerations, planning and robustness in isolation. But a global view of energy awareness that considers these factors and looks at various tradeoffs is essential. To this end, we present results from our detailed empirical study of battery charge-discharge characteristics and the impact of altitude and lighting on edge inference accuracy. Our energy models, derived from these observations, predict energy usage while performing various manoeuvres with an error of 5.6%, a 2.5X improvement over the state-of-the-art. Furthermore, we propose a holistic energy-aware multi-drone scheduling system that decreases the energy consumed by 21.14% and the mission times by 46.91% over state-of-the-art baselines. To achieve system robustness in the event of link or drone failure, we observe trends in Packet Delivery Ratio to propose a methodology to establish reliable communication between nodes. We release an open-source implementation of our system. Finally, we tie all of these pieces together using a people-counting case study.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"116 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139559110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PAM-FOG Net: A Lightweight Weed Detection Model Deployed on Smart Weeding Robots PAM-FOG Net：部署在智能除草机器人上的轻量级杂草检测模型

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-22 DOI: 10.1145/3641821

Jiahua Bao, Siyao Cheng, Jie Liu

{"title":"PAM-FOG Net: A Lightweight Weed Detection Model Deployed on Smart Weeding Robots","authors":"Jiahua Bao, Siyao Cheng, Jie Liu","doi":"10.1145/3641821","DOIUrl":"https://doi.org/10.1145/3641821","url":null,"abstract":"Visual target detection based on deep learning with high computing power devices has been successful, but the performance in intelligent agriculture with edge devices has not been prominent. Specifically, the existing model architecture and optimization methods are not well-suited to low-power edge devices, the agricultural tasks such as weed detection require high accuracy, short inference latency, and low cost. Although there are automated tuning methods available, the search space is extremely large, using existing models for compression and optimization greatly wastes tuning resources. In this article, we propose a lightweight PAM-FOG net based on weed distribution and projection mapping. More significantly, we propose a novel model compression optimization method to fit our model. Compared with other models, PAM-FOG net runs on smart weeding robots supported by edge devices, and achieves superior accuracy and high frame rate. We effectively balance model size, performance and inference speed, reducing the original model size by nearly 50%, power consumption by 26%, and improving the frame rate by 40%. It shows the effectiveness of our model architecture and optimization method, which provides a reference for the future development of deep learning in intelligent agriculture.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"15 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139515383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tensor-Based Viterbi Algorithms for Collaborative Cloud-Edge Cyber-Physical-Social Activity Prediction 基于张量的维特比算法用于云边缘网络-物理-社交活动协同预测

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-17 DOI: 10.1145/3639467

Shunli Zhang, Laurence T. Yang, Yue Zhang, Zhixing Lu, Zongmin Cui

{"title":"Tensor-Based Viterbi Algorithms for Collaborative Cloud-Edge Cyber-Physical-Social Activity Prediction","authors":"Shunli Zhang, Laurence T. Yang, Yue Zhang, Zhixing Lu, Zongmin Cui","doi":"10.1145/3639467","DOIUrl":"https://doi.org/10.1145/3639467","url":null,"abstract":"With the rapid development and application of smart city, Cyber-Physical-Social Systems (CPSS) as its superset is becoming increasingly important, and attracts extensive attentions. For satisfying the smart requirements of CPSS design, a cloud-edge collaborative CPSS framework is first proposed in this paper. Then Coupled-Hidden-Markov-Model (CHMM) and tensor algebra are used to improve existing activity prediction methods for providing CPSS with more intelligent decision support. There are three key features (timing, periodicity and correlation) implied in CPSS data from multi-edge, which affects the accuracy of activity prediction. Thus, these features are synthetically integrated into improved Tensor-based CHMMs (T-CHMMs) to enhance the prediction accuracy. Based on the multi-edge CPSS data, three Tensor-based Viterbi Algorithms (TVA) are correspondingly proposed to solve the prediction problem for T-CHMMs. Compared with traditional matrix-based methods, the proposed TVA could more accurately compute the optimal hidden state sequences under given observation sequences. Finally, the comprehensive performances of proposed models and algorithms are validated on three open datasets by self-comparison and other-comparison. The experimental results show that the proposed methods is superior to the compared three classical methods in terms of F1 measure, average precision and average recall.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"1 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139481940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Learning Mechanisms for Anomaly Detection in Privacy-Aware Energy Grid Management Systems 隐私意识能源网管理系统中异常检测的分布式学习机制

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-17 DOI: 10.1145/3640341

Jia-Hao Syu, Jerry Chun-Wei Lin, Gautam Srivastava

{"title":"Distributed Learning Mechanisms for Anomaly Detection in Privacy-Aware Energy Grid Management Systems","authors":"Jia-Hao Syu, Jerry Chun-Wei Lin, Gautam Srivastava","doi":"10.1145/3640341","DOIUrl":"https://doi.org/10.1145/3640341","url":null,"abstract":"Smart grids have become an emerging topic due to net-zero emissions and the rapid development of artificial intelligence (AI) technology focused on achieving targeted energy distribution and maintaining operating reserves. In order to prevent cyber-physical attacks, issues related to the security and privacy of grid systems are receiving much attention from researchers. In this paper, privacy-aware energy grid management systems with anomaly detection networks and distributed learning mechanisms are proposed. The anomaly detection network consists of a server and a client learning network, which collaboratively learn patterns without sharing data, and periodically train and exchange knowledge. We also develop learning mechanisms with federated, distributed, and split learning to improve privacy and use Q-learning for decision-making to facilitate interpretability. To demonstrate the effectiveness and robustness of the proposed schemes, extensive simulations are conducted in different energy grid environments with different target distributions, ORRs, and attack scenarios. The experimental results show that the proposed schemes not only improve management performance but also enhance privacy and security levels. We also compare the management performance and privacy level of the different learning machines and provide usage recommendations.","PeriodicalId":50910,"journal":{"name":"ACM Transactions on Sensor Networks","volume":"139 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139481942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimize the Age of Useful Information in Edge-Assisted Energy Harvesting Sensor Networks 优化边缘辅助能量收集传感器网络中的有用信息年龄

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-11 DOI: 10.1145/3640342

Tuo Shi, Zhipeng Cai, Jianzhong Li, Hong Gao

引用次数: 0

Editorial: Special Issue on Cyber-Physical Security and Zero Trust 社论：网络物理安全与零信任特刊

IF 4.1 4区计算机科学

ACM Transactions on Sensor Networks Pub Date : 2024-01-10 DOI: 10.1145/3634700

Fangyu Li, Wenzhan Song, Xiaohua Xu

引用次数: 0