{"id":970509,"date":"2023-11-08T05:54:00","date_gmt":"2023-11-08T13:54:00","guid":{"rendered":"https:\/\/www.microsoft.com\/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:\/\/www.microsoft.com\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-970509","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2023-11-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"ACM","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/09\/HotNets_2023_Paper.pdf","id":"982497","title":"hotnets_2023_paper","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":982497,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/11\/HotNets_2023_Paper.pdf"}],"msr-author-ordering":[{"type":"text","value":"Rahul Bothra","user_id":0,"rest_url":false},{"type":"text","value":"Aryan Taneja","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Debopam Bhattacherjee","user_id":41048,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Debopam Bhattacherjee"},{"type":"user_nicename","value":"Rohan Gandhi","user_id":42372,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Rohan Gandhi"},{"type":"user_nicename","value":"Venkat Padmanabhan","user_id":33180,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Venkat Padmanabhan"},{"type":"text","value":"Ranjita Bhagwan","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Nagarajan Natarajan","user_id":37311,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Nagarajan Natarajan"},{"type":"user_nicename","value":"Saikat Guha","user_id":33493,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Saikat Guha"},{"type":"user_nicename","value":"Ross Cutler","user_id":40660,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ross Cutler"}],"msr_impact_theme":[],"msr_research_lab":[199562],"msr_event":[],"msr_group":[144725],"msr_project":[887322],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":887322,"post_title":"Network Brain","post_name":"netbrain","post_type":"msr-project","post_date":"2022-10-17 05:39:45","post_modified":"2023-11-02 01:11:16","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/netbrain\/","post_excerpt":"Holistic optimization of large-scale networked services The growth of large-scale networked services has brought to the fore myriad challenges: performance, reliability, efficiency, cost, and more. Traditionally, work on addressing and balancing these has been done in silos. For instance, an application could make choices to optimize its own performance or cost, while treating the rest of the workload and infrastructure as outside its purview. However, such an approach breaks down when an application or service…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/887322"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/970509"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/970509\/revisions"}],"predecessor-version":[{"id":970512,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/970509\/revisions\/970512"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=970509"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=970509"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=970509"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=970509"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=970509"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=970509"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=970509"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=970509"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=970509"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=970509"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=970509"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=970509"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=970509"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=970509"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=970509"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=970509"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}