{"id":579094,"date":"2019-04-15T11:36:01","date_gmt":"2019-04-15T18:36:01","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=579094"},"modified":"2019-04-15T11:36:01","modified_gmt":"2019-04-15T18:36:01","slug":"pegasus-load-aware-selective-replication-with-an-in-network-coherence-directory","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/pegasus-load-aware-selective-replication-with-an-in-network-coherence-directory\/","title":{"rendered":"Pegasus: Load-Aware Selective Replication with an In-Network Coherence Directory"},"content":{"rendered":"
High performance distributed storage systems face the challenge of load imbalance caused by skewed and dynamic workloads. This paper introduces Pegasus, a new storage architecture that leverages new-generation programmable switch ASICs to balance load across storage servers. Pegasus uses selective replication of the most popular objects in the data store to distribute load. Using a […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193718],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-579094","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":"2018-12","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":"UW-CSE-18-12-01","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"University of Washington","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\/2019\/04\/pegasus-tr18.pdf","id":"579097","title":"pegasus-tr18","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":579097,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/04\/pegasus-tr18.pdf"}],"msr-author-ordering":[{"type":"text","value":"Jialin Li","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Jacob Nelson","user_id":36275,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jacob Nelson"},{"type":"text","value":"Xin Jin","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Dan R. 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