{"title":"利用边缘和云技术打造个性化无人机队移动应用平台","authors":"Suman Raj, Yogesh L. Simmhan","doi":"10.1109/CCGridW59191.2023.00075","DOIUrl":null,"url":null,"abstract":"Advances in edge computing, accelerators, computer vision, and artificial intelligence have led to the widespread application of autonomous vehicles such as drones. Besides logistics and urban safety, drones can also be used for social good. In this paper, we present the outline for a lightweight mobile app platform that can be used by the visually impaired for navigational assistance. The platform uses an intelligent middleware scheduler to perform DNN inferencing either on the onboard edge device or offloads it to a FaaS running on the cloud, while maximizing utility and the tasks processed. We validate our platform for multiple workloads, supporting up to 4 drones per edge device, with 7 edges running concurrently and using AWS Lambda as the remote cloud. We also test our platform using Jetson Nano and Tello drones as hardware validation.","PeriodicalId":341115,"journal":{"name":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Towards a Mobile App Platform for Personalized UAV Fleets using Edge and Cloud\",\"authors\":\"Suman Raj, Yogesh L. Simmhan\",\"doi\":\"10.1109/CCGridW59191.2023.00075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Advances in edge computing, accelerators, computer vision, and artificial intelligence have led to the widespread application of autonomous vehicles such as drones. Besides logistics and urban safety, drones can also be used for social good. In this paper, we present the outline for a lightweight mobile app platform that can be used by the visually impaired for navigational assistance. The platform uses an intelligent middleware scheduler to perform DNN inferencing either on the onboard edge device or offloads it to a FaaS running on the cloud, while maximizing utility and the tasks processed. We validate our platform for multiple workloads, supporting up to 4 drones per edge device, with 7 edges running concurrently and using AWS Lambda as the remote cloud. We also test our platform using Jetson Nano and Tello drones as hardware validation.\",\"PeriodicalId\":341115,\"journal\":{\"name\":\"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCGridW59191.2023.00075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGridW59191.2023.00075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a Mobile App Platform for Personalized UAV Fleets using Edge and Cloud
Advances in edge computing, accelerators, computer vision, and artificial intelligence have led to the widespread application of autonomous vehicles such as drones. Besides logistics and urban safety, drones can also be used for social good. In this paper, we present the outline for a lightweight mobile app platform that can be used by the visually impaired for navigational assistance. The platform uses an intelligent middleware scheduler to perform DNN inferencing either on the onboard edge device or offloads it to a FaaS running on the cloud, while maximizing utility and the tasks processed. We validate our platform for multiple workloads, supporting up to 4 drones per edge device, with 7 edges running concurrently and using AWS Lambda as the remote cloud. We also test our platform using Jetson Nano and Tello drones as hardware validation.
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