{"title":"Experience: a five-year retrospective of MobileInsight","authors":"Yuanjie Li, Chunyi Peng, Zhehui Zhang, Zhaowei Tan, Haotian Deng, Jinghao Zhao, Qianru Li, Yunqi Guo, Kai Ling, Boyan Ding, Hewu Li, Songwu Lu","doi":"10.1145/3447993.3448138","DOIUrl":null,"url":null,"abstract":"This paper reports our five-year lessons of developing and using MobileInsight, an open-source community tool to enable software-defined full-stack, runtime mobile network analytics inside our phones. We present how MobileInsight evolves from a simple monitor to a community toolset with cross-layer analytics, energy-efficient real-time user-plane analytics, and extensible user-friendly analytics at the control and user planes. These features are enabled by various novel techniques, including cross-layer state machine tracking, missing data inference, and domain-specific cross-layer sampling. Their powerfulness is exemplified with a 5-year longitudinal study of operational mobile network latency using a 6.4TB dataset with 6.1 billion over-the-air messages. We further share lessons and insights of using MobileInsight by the community, as well as our visions of MobileInsight's past, present, and future.","PeriodicalId":177431,"journal":{"name":"Proceedings of the 27th Annual International Conference on Mobile Computing and Networking","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th Annual International Conference on Mobile Computing and Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3447993.3448138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
This paper reports our five-year lessons of developing and using MobileInsight, an open-source community tool to enable software-defined full-stack, runtime mobile network analytics inside our phones. We present how MobileInsight evolves from a simple monitor to a community toolset with cross-layer analytics, energy-efficient real-time user-plane analytics, and extensible user-friendly analytics at the control and user planes. These features are enabled by various novel techniques, including cross-layer state machine tracking, missing data inference, and domain-specific cross-layer sampling. Their powerfulness is exemplified with a 5-year longitudinal study of operational mobile network latency using a 6.4TB dataset with 6.1 billion over-the-air messages. We further share lessons and insights of using MobileInsight by the community, as well as our visions of MobileInsight's past, present, and future.