{"title":"MIQA:毫米波上沉浸式内容交付的应用代理","authors":"Zongshen Wu;Chin-Ya Huang;Parameswaran Ramanathan","doi":"10.1109/TMC.2024.3514973","DOIUrl":null,"url":null,"abstract":"The highly directional nature of the millimeter wave (mmWave) beams causes several challenges in using that spectrum to meet the communication demands of immersive applications. The mmWave beams are especially susceptible to misalignments and blockages caused by user movements. As a result, mmWave channels are vulnerable to large quality fluctuations, which in turn, degrades the end-to-end performance of immersive applications. In this paper, we propose a reinforcement learning (RL) based application-layer plugin that works in conjunction with the QUIC protocol to combat the challenges of mmWave networks. The plug-in called Millimeter wave based Immersive QUIC Agent (MIQA) uses the RL model to help modulate the sending rate along with the congestion control scheme of QUIC. To evaluate the effectiveness of MIQA, we conduct experiments on a mmWave augmented immersive testbed. The evaluation results show that MIQA significantly improves the immersive experience by increasing the end-to-end throughput and by decreasing the end-to-end latency.","PeriodicalId":50389,"journal":{"name":"IEEE Transactions on Mobile Computing","volume":"24 5","pages":"3750-3763"},"PeriodicalIF":7.7000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MIQA: An Application Agent for Immersive Content Delivery Over Millimeter Waves\",\"authors\":\"Zongshen Wu;Chin-Ya Huang;Parameswaran Ramanathan\",\"doi\":\"10.1109/TMC.2024.3514973\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The highly directional nature of the millimeter wave (mmWave) beams causes several challenges in using that spectrum to meet the communication demands of immersive applications. The mmWave beams are especially susceptible to misalignments and blockages caused by user movements. As a result, mmWave channels are vulnerable to large quality fluctuations, which in turn, degrades the end-to-end performance of immersive applications. In this paper, we propose a reinforcement learning (RL) based application-layer plugin that works in conjunction with the QUIC protocol to combat the challenges of mmWave networks. The plug-in called Millimeter wave based Immersive QUIC Agent (MIQA) uses the RL model to help modulate the sending rate along with the congestion control scheme of QUIC. To evaluate the effectiveness of MIQA, we conduct experiments on a mmWave augmented immersive testbed. The evaluation results show that MIQA significantly improves the immersive experience by increasing the end-to-end throughput and by decreasing the end-to-end latency.\",\"PeriodicalId\":50389,\"journal\":{\"name\":\"IEEE Transactions on Mobile Computing\",\"volume\":\"24 5\",\"pages\":\"3750-3763\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2024-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Mobile Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10788519/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Mobile Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10788519/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
MIQA: An Application Agent for Immersive Content Delivery Over Millimeter Waves
The highly directional nature of the millimeter wave (mmWave) beams causes several challenges in using that spectrum to meet the communication demands of immersive applications. The mmWave beams are especially susceptible to misalignments and blockages caused by user movements. As a result, mmWave channels are vulnerable to large quality fluctuations, which in turn, degrades the end-to-end performance of immersive applications. In this paper, we propose a reinforcement learning (RL) based application-layer plugin that works in conjunction with the QUIC protocol to combat the challenges of mmWave networks. The plug-in called Millimeter wave based Immersive QUIC Agent (MIQA) uses the RL model to help modulate the sending rate along with the congestion control scheme of QUIC. To evaluate the effectiveness of MIQA, we conduct experiments on a mmWave augmented immersive testbed. The evaluation results show that MIQA significantly improves the immersive experience by increasing the end-to-end throughput and by decreasing the end-to-end latency.
期刊介绍:
IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.