Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications最新文献

{"title":"Secure Drone Identification with Hyperledger Iroha","authors":"Yousef Hashem, Elmedin Zildzic, A. Gurtov","doi":"10.1145/3479243.3487305","DOIUrl":"https://doi.org/10.1145/3479243.3487305","url":null,"abstract":"Interet-of-Things (IoT) devices such as drones are becoming more prevalent, but still have blatant security issues. DRIP is a newly proposed protocol for drones that aims to enable users to securely identify drones and trust in messages sent by them. However, some implementation details, such as registries, are yet to be determined. The decentralization, auditability and persistency of blockchain makes it a great candidate to be used as a registry in DRIP. This paper analyzes how Hyperledger Iroha, a permission-based blockchain framework, can be used to fulfill the registry requirements in DRIP, and propose an architecture using it as a registry. Findings show that, thanks to its support for various permissions, multi-signature transactions, and smart contracts, it is able to not only fulfill the requirements, but also enhance other security details of the proposed architecture. Furthermore, this paper also evaluates the performance of Iroha, with results showing that its low consensus delay is adequate to be used for real-time location updates.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131017041","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}

{"title":"Tutorial: Edge Computing for Mobile Internet of Things","authors":"Rodolfo W. L. Coutinho","doi":"10.1145/3479243.3494705","DOIUrl":"https://doi.org/10.1145/3479243.3494705","url":null,"abstract":"Internet of things (IoT) has emerged as the enabling technology for smart applications in different domains, such as transportation, health-care, industry, smart homes and buildings, and education (e.g., [1-5]). IoT applications rely on the deployment of resourceconstrained devices that collect data from the environment it is immersed and control events of interest through actuators. One of the daunting challenges in many IoT applications is the need for the real-time processing of a large amount of produced data. Such processing is often impractical to be performed at the IoT devices, due to their resource-constrained nature and the incurred energy cost. In this regard, IoT data is often offloaded to be processed on distant powerful cloud servers, which return to IoT devices as the result of the heavy computations. This approach is well-suited for computation-intensive tasks in IoT applications. However, the process of task offloading to cloud servers incurs additional delays for the IoT application, in addition to the network overhead. Therefore, edge computing has been proposed to provide computation, communication, and storage resources closer to IoT devices. The general idea is to place resources in the proximity of IoT devices that will demand them. Thus, the latency involved in the IoT application is reduced since computation-intensive tasks are processed on edge devices rather than on distant cloud servers. One of the critical challenges in edge-aided IoT applications is that edge devices have limited resource capabilities when compared to cloud servers. In this regard, edge devices' resources must be managed and allocated in an efficient way, aimed at providing resources to IoT applications with guaranteed quality of service (QoS). This tutorial will motivate and explore the challenges, design principles, and goals of edge computing for IoT applications. It presents the building blocks for the design of optimization models for IoT task offloading to edge nodes. By doing so, it discusses the communication challenges between IoT and edge devices and highlights the different mathematical formulations commonly used in the literature to model IoT to edge communication. Furthermore, this tutorial discusses optimization-based and machine learning (ML)-based solutions for tackling the task offloading decision problem. Besides, this tutorial presents recent advancements in resource management solutions aimed at efficient resource allocation at edge devices. Finally, this tutorial shall conclude with a discussion of research opportunities and challenges in the edge-assisted Internet of things.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128116526","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}

{"title":"A Novel Dynamic Split and Merge Clustering Scheme for SDVN","authors":"Noura Aljeri, A. Boukerche","doi":"10.1145/3479243.3487307","DOIUrl":"https://doi.org/10.1145/3479243.3487307","url":null,"abstract":"With the start of a new era of Intelligently Connected Vehicular Networks, the communication in vehicular networks is no longer limited to vehicle-to-vehicle and vehicle-to-infrastructure but also expands to vehicle-to-pedestrian, vehicle-to-grid vehicle-to-device, collectively referred to as vehicle-to-everything (V2X). Network softwarization is an essential attribute to address the challenges in heterogeneous networks through share interface platform an control. However, it brings several issues to the topology design of software-defined vehicular networks. In this paper, we propose a dynamic split and merge-based clustering method for software-defined vehicular networks. The proposed method adaptively change the network's topology based on latency, load, and traffic-flow. The proposed scheme is evaluated under realistic mobility and network structure. The results indicate the efficiency of the proposed scheme in terms of latency and load on network entities.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125890995","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}

{"title":"Autonomous Vehicle Navigation and Communication by Passive Radio Frequency (RFID) Tags","authors":"Osama Javaid, F. Yu, Junrun Huang","doi":"10.1145/3479243.3487303","DOIUrl":"https://doi.org/10.1145/3479243.3487303","url":null,"abstract":"This paper assesses the feasibility of using Passive UHF Radio-Frequency Identity (RFID) tags to augment the existing technologies for Autonomous Vehicle (AV) limitations such as camera occlusions, traffic-sign tempering, and spotty GPS signals interrupting AV localization. The study finds the Received Signal Strength Indicator (RSSI) and the number of tag reads in various propagation mediums such as Ice, Water, and Snow with single and dual-antenna configurations. A reader was mounted onto the AV, and readings were collected by driving it over the tags. Experiments were conducted with an AV on a test track with speeds up to 90 km/h. Due to the track constraints, speeds higher than that could not be tried. One research, however, was able to read the Passive tags up to 200 km/h. This paper finds that the technology in its current form is suitable for controlled indoor and confined environments. However, if more antennas and readers are experimented with - and more Passive RFID equipment is developed for AVs, it could show promise against the current AV limitations.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115321185","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}

{"title":"Flexi-Compression: A Flexible Model Compression Method for Autonomous Driving","authors":"Hantao Liu, Ying He, F. Yu, Jeremy James","doi":"10.1145/3479243.3487300","DOIUrl":"https://doi.org/10.1145/3479243.3487300","url":null,"abstract":"Benefiting from the rapid development of convolutional neural networks, computer vision-based autonomous driving technologies are gradually being deployed in vehicles. However, these neural networks typically have a large number of parameters and extremely high computational cost, making them difficult to deploy in autonomous vehicles with limited storage and computational power. In this paper, we propose an innovative model compression approach to compress convolutional neural networks in autonomous driving algorithms, which we call Flexi-Compression. Flexi-Compression first modifies the model structure by replacing the traditional convolutional layers with our proposed Flexi-CP module, thus reducing the computation of the convolutional layers. Then, we leverage knowledge distillation to enable the compressed model to quickly acquire the knowledge of the original model. In addition, we use a Flexi-Batch Normalization layer to prune the model and finally further reduce the model size by model quantization. We compress the VGG-16 network using our proposed model compression algorithm, which is a commonly used backbone network in autonomous driving algorithms. On the CIFAR-10 dataset, our compression method can reduce the parameters of the VGG-16 network by 86% and the computation by 87% with 4% loss of accuracy. To verify the effectiveness of our compression algorithm in real-world applications, we also compress an autonomous driving algorithm and achieve excellent performance.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124454330","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}

{"title":"Interference-Aware Trajectory Optimization for Cellular-connected UAVs with Obstacle Avoidance","authors":"Elhadja Chaalal, L. Reynaud, S. Senouci","doi":"10.1145/3479243.3487294","DOIUrl":"https://doi.org/10.1145/3479243.3487294","url":null,"abstract":"In this paper, the problem of finding the optimal trajectory for a cellular-connected unmanned aerial vehicle (UAV), in a 3D environment with obstacles is studied. In particular, the UAV flies from an initial point to a destination point and must maintain a good connectivity with the ground cellular network. Moreover, the resulting trajectory should minimize the emerging interference signals that the ground base stations (GBSs) receive from the UAV. To solve this problem, a probabilistic roadmap (PRM) is constructed first to generate the practical graph for traveling through the area of interest and avoid all type of obstacles. The resulting collision-free interference-aware roadmap illustrates the possible collision-free cellular-connected paths, where the UAV is guaranteed to have a good connectivity with the network, and their corresponding ground interference levels. Then, a shortest path algorithm is used to find the optimal path, with the least interference effects. Simulation results further validate the performance of our proposed scheme and show that it achieves better coverage rates and generates less interference when compared to other schemes, that do not account the cellular communication metrics. Indeed, our proposed solution guarantees a 100% connectivity rate, and generates a total interference of 22 dBm, as compared to the two other schemes that generate interference levels of 26 dBm and 27 dBm.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115234126","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}

{"title":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","authors":"","doi":"10.1145/3479243","DOIUrl":"https://doi.org/10.1145/3479243","url":null,"abstract":"","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133487077","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}

{"title":"Secure Computational Offloading with gRPC: A Performance Evaluation in a Mobile Cloud Computing Environment","authors":"Filipe Fernandes S. B. de Matos, P. Rego, Fernando A. M. Trinta","doi":"10.1145/3479243.3487295","DOIUrl":"https://doi.org/10.1145/3479243.3487295","url":null,"abstract":"Computational offloading is a technique commonly indicated to mitigate computational and energy constraints on mobile devices. However, this procedure occurs over a wireless network, an insecure environment, and susceptible to attacks. Currently, one of the main problems related to offloading is how to perform it safely. By acting in conjunction with the TLS protocol, secure gRPC connections ensure the authenticity and integrity of the data transmitted through a network, which provides greater security for distributed applications. In this work, we conducted experiments that evaluated the performance of secure gRPC connections during the computational offloading procedures in a Mobile Cloud Computing scenario. The tests adopted an Android image manipulation application that performs the offloading into a Go or Java process using the multi-language framework gRPC. The results indicated that the adoption of secure gRPC connections saved up to 9 times the processing time and up to 88% of the mobile device's energy consumption compared to local processing.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"3 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120840550","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}

{"title":"TTWiFi: Time-Triggered Communication over WiFi","authors":"Carl Lusty, V. Estivill-Castro, R. Hexel","doi":"10.1145/3479243.3487298","DOIUrl":"https://doi.org/10.1145/3479243.3487298","url":null,"abstract":"WiFi is prevalent in mobile robotics and the Internet of Things (IoT) despite the fact that many applications in these environments require real-time communication. WiFi does not guarantee timeliness and often introduces unbounded communication delays. We present TTWiFi, a time-triggered protocol for fault-tolerant real-time communication between devices situated in a broadcast domain, that only requires minor changes to IEEE 802.11 parameters and remains standards-compliant in critical aspects. We implemented TTWiFi on a representative platform and benchmarked our implementation with TCP and UDP over unmodified WiFi. Our results demonstrate that unlike the latter, TTWiFi has the ability to maintain communication in a congested environment while exhibiting fail-silent behaviour crucial for fault tolerance and real-time communication.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131583594","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}

{"title":"Edge-based V2X Efficient Traffic Emergency Responding Protocol","authors":"Aaron Ayub, Thiago S. Gomides, Robson E. De Grande","doi":"10.1145/3479243.3487309","DOIUrl":"https://doi.org/10.1145/3479243.3487309","url":null,"abstract":"Traffic accidents considerably hinder transportation in urban centres, bringing high socio-economic costs. More importantly, an accident can severely compromise the health and lives of individuals. Minimizing the access time of an emergency response vehicle (ERV) to an accident site reduces damages, losses, and costs considerably. Traffic management systems (TMS) solutions ease the traffic congestion levels through recommended alternative re-routed paths. However, even though TMS might positively and indirectly aid ERV access, there is no focus on efficiently reducing ERV access time. Thus, a VANET-based approach is proposed to facilitate the timely arrival of an ERV to a destination. The approach uses multi-hop, ad-hoc messages between ordinary connected vehicles, the network edge, and ERVs to communicate details on an accident and coordinate a response. Results show that accident resolution can outperform congestion mitigation methods and demonstrate that ERV selection based on proximity reduces response time.","PeriodicalId":300054,"journal":{"name":"Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125212538","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}