{"id":970509,"date":"2023-11-08T05:54:00","date_gmt":"2023-11-08T13:54:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/?post_type=msr-research-item&p=970509"},"modified":"2023-11-08T05:54:00","modified_gmt":"2023-11-08T13:54:00","slug":"dont-forget-the-user-its-time-to-rethink-network-measurements","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/dont-forget-the-user-its-time-to-rethink-network-measurements\/","title":{"rendered":"Don\u2019t Forget the User: It\u2019s Time to Rethink Network Measurements"},"content":{"rendered":"

Network measurement has long focused on the bits and <\/span>bytes \u2014 low-level network metrics such as latency and <\/span>throughput, which have the advantage of being objective and <\/span>directly characterizing the performance of the network. We <\/span>argue that users provide a rich and largely untapped source <\/span>of<\/span> implicit<\/span> as well as<\/span> explicit<\/span> signals that could complement <\/span>and expand the coverage of traditional methods.<\/span> Implicit <\/span>feedback leverages user actions to indirectly infer the net<\/span>work performance and the resulting quality of user experi<\/span>ence. Explicit feedback leverages user input, typically pro<\/span>vided offline, to expand the reach of network measurement, <\/span>especially for newer ones.<\/span><\/p>\n

We analyse two scenarios \u2013 capturing implicit feedback <\/span>through user actions from a large-scale conferencing service, <\/span>and gathering explicit feedback via social media posts per<\/span>taining to the SpaceX Starlink Low Earth Orbit (LEO) satel<\/span>lite network undergoing deployment. We believe our tech<\/span>niques complement the traditional measurement methods <\/span>and opens a broad set of research directions, ranging from re<\/span>thinking measurements tools, to designing user-centric net<\/span>worked systems and applications.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Network measurement has long focused on the bits and bytes \u2014 low-level network metrics such as latency and throughput, which have the advantage of being objective and directly characterizing the performance of the network. We argue that users provide a rich and largely untapped source of implicit as well as explicit signals that could complement […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"ACM","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"ACM 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