{"title":"海报:启用灵活的边缘辅助XR","authors":"Jin Heo, Ketan Bhardwaj, Ada Gavrilovska","doi":"10.1145/3453142.3491408","DOIUrl":null,"url":null,"abstract":"Extended reality (XR) is touted as the next frontier of the digital future. XR includes all immersive technologies of augmented reality (AR), virtual reality (VR), and mixed reality (MR). XR applications obtain the real-world context of the user from an underlying system, and provide rich, immersive, and interactive virtual experiences based on the user's context in real-time. XR systems process streams of data from device sensors, and provide functionalities including perceptions and graphics required by the applications. These processing steps are computationally intensive, and the challenge is that they must be performed within the strict latency requirements of XR. This poses limitations on the possible XR experiences that can be supported on mobile devices with limited computing resources. In this XR context, edge computing is an effective approach to address this problem for mobile users. The edge is located closer to the end users and enables processing and storing data near them. In addition, the development of high bandwidth and low latency network technologies such as 5G facilitates the application of edge computing for latency-critical use cases [4], [11]. This work presents an XR system for enabling flexible edge-assisted XR.","PeriodicalId":6779,"journal":{"name":"2021 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"14 1","pages":"465-467"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Poster: Enabling Flexible Edge-assisted XR\",\"authors\":\"Jin Heo, Ketan Bhardwaj, Ada Gavrilovska\",\"doi\":\"10.1145/3453142.3491408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Extended reality (XR) is touted as the next frontier of the digital future. XR includes all immersive technologies of augmented reality (AR), virtual reality (VR), and mixed reality (MR). XR applications obtain the real-world context of the user from an underlying system, and provide rich, immersive, and interactive virtual experiences based on the user's context in real-time. XR systems process streams of data from device sensors, and provide functionalities including perceptions and graphics required by the applications. These processing steps are computationally intensive, and the challenge is that they must be performed within the strict latency requirements of XR. This poses limitations on the possible XR experiences that can be supported on mobile devices with limited computing resources. In this XR context, edge computing is an effective approach to address this problem for mobile users. The edge is located closer to the end users and enables processing and storing data near them. In addition, the development of high bandwidth and low latency network technologies such as 5G facilitates the application of edge computing for latency-critical use cases [4], [11]. This work presents an XR system for enabling flexible edge-assisted XR.\",\"PeriodicalId\":6779,\"journal\":{\"name\":\"2021 IEEE/ACM Symposium on Edge Computing (SEC)\",\"volume\":\"14 1\",\"pages\":\"465-467\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE/ACM Symposium on Edge Computing (SEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3453142.3491408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACM Symposium on Edge Computing (SEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3453142.3491408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extended reality (XR) is touted as the next frontier of the digital future. XR includes all immersive technologies of augmented reality (AR), virtual reality (VR), and mixed reality (MR). XR applications obtain the real-world context of the user from an underlying system, and provide rich, immersive, and interactive virtual experiences based on the user's context in real-time. XR systems process streams of data from device sensors, and provide functionalities including perceptions and graphics required by the applications. These processing steps are computationally intensive, and the challenge is that they must be performed within the strict latency requirements of XR. This poses limitations on the possible XR experiences that can be supported on mobile devices with limited computing resources. In this XR context, edge computing is an effective approach to address this problem for mobile users. The edge is located closer to the end users and enables processing and storing data near them. In addition, the development of high bandwidth and low latency network technologies such as 5G facilitates the application of edge computing for latency-critical use cases [4], [11]. This work presents an XR system for enabling flexible edge-assisted XR.