{"id":161997,"date":"2012-05-01T00:00:00","date_gmt":"2012-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/race-real-time-applications-over-cloud-edge\/"},"modified":"2018-10-16T20:05:47","modified_gmt":"2018-10-17T03:05:47","slug":"race-real-time-applications-over-cloud-edge","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/race-real-time-applications-over-cloud-edge\/","title":{"rendered":"RACE: Real-time Applications over Cloud-Edge"},"content":{"rendered":"
\n

The Cloud-Edge topology – where multiple smart edge devices such as phones are connected to one another via the Cloud – is becoming ubiquitous. We demonstrate RACE, a new framework and system for specifying and efficiently executing distributed real-time applications in the Cloud-Edge topology. RACE uses LINQ for StreamInsight to succinctly express a diverse suite of useful real-time applications. Further, it exploits the processing power of edge devices and the Cloud to partition and execute such queries in a distributed manner. RACE features a novel cost-based optimizer that efficiently finds the optimal placement, minimizing global communication cost while handling multi-level join queries and asymmetric network links.<\/p>\n<\/div>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

The Cloud-Edge topology – where multiple smart edge devices such as phones are connected to one another via the Cloud – is becoming ubiquitous. We demonstrate RACE, a new framework and system for specifying and efficiently executing distributed real-time applications in the Cloud-Edge topology. RACE uses LINQ for StreamInsight to succinctly express a diverse suite […]<\/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-161997","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM SIGMOD","msr_edition":"ACM SIGMOD International Conference on Management of Data (SIGMOD 2012)","msr_affiliation":"","msr_published_date":"2012-05-01","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":"","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":"206028","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"race-sigmod2012-demo.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/race-sigmod2012-demo.pdf","id":206028,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":206028,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/race-sigmod2012-demo.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"badrishc","user_id":31166,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=badrishc"},{"type":"user_nicename","value":"jorisc","user_id":32398,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=jorisc"},{"type":"user_nicename","value":"sumann","user_id":33753,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=sumann"},{"type":"user_nicename","value":"ivosan","user_id":32130,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=ivosan"},{"type":"text","value":"Wenchao Zhou","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[957177],"msr_project":[170875],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":170875,"post_title":"Streams","post_name":"streams","post_type":"msr-project","post_date":"2011-11-21 13:31:30","post_modified":"2017-06-19 10:26:41","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/streams\/","post_excerpt":"In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. 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