{"id":896829,"date":"2022-11-08T15:31:13","date_gmt":"2022-11-08T23:31:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2022-11-08T15:31:13","modified_gmt":"2022-11-08T23:31:13","slug":"hydra-serialization-free-network-ordering-for-strongly-consistent-distributed-applications","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/hydra-serialization-free-network-ordering-for-strongly-consistent-distributed-applications\/","title":{"rendered":"Hydra: Serialization-Free Network Ordering for Strongly Consistent Distributed Applications"},"content":{"rendered":"<div class=\"row\">\n<div class=\"col datacolumn\">\n<div class=\"pub-details\">\n<div class=\"abstract well\" data-ex-content=\".abstract\">A large class of distributed systems, e.g., state machine replication and fault-tolerant distributed databases, rely on establishing a consistent order of operations on groups of nodes in the system. Traditionally, an application-level distributed protocol such as Paxos and two-phase locking provide the ordering guarantees. To reduce the performance overhead imposed by these protocols, a recent line of work propose to move the responsibility of ensuring operation ordering into the network by sequencing requests through a centralized network sequencer. This network sequencing approach yields significant application-level performance improvements, but routing all requests through a single sequencer comes with several fundamental limitations, including sequencer scalability bottleneck, prolonged system downtime during sequencer failover, worsened network-level load balancing, etc.Our work, Hydra, overcomes these limitations by using a distributed set of network sequencers to provide network ordering. Hydra leverages loosely synchronized clocks on network sequencers to establish message ordering across them, per-sequencer sequence numbers to detect message drops, and periodic timestamp messages to enforce progress when some sequencers are idle. To demonstrate the benefit of Hydra, we co-designed a state machine replication protocol and a distributed transactional system using the Hydra network primitive. Compared to serialization-based network ordering systems, Hydra shows equivalent performance improvement over traditional approaches in both applications, but with significantly higher scalability, shorter sequencer failover time, and better network-level load balancing.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>A large class of distributed systems, e.g., state machine replication and fault-tolerant distributed databases, rely on establishing a consistent order of operations on groups of nodes in the system. Traditionally, an application-level distributed protocol such as Paxos and two-phase locking provide the ordering guarantees. To reduce the performance overhead imposed by these protocols, a recent [&hellip;]<\/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":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"20th USENIX Symposium on Networked Systems Design and Implementation (NSDI '23)","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2023-4","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[258469],"msr-conference":[263941],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-896829","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us","msr-field-of-study-networking"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2023-4","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":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2022\/11\/hydra-nsdi23.pdf","id":"896832","title":"hydra-nsdi23","label_id":"243109","label":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[{"id":896832,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2022\/11\/hydra-nsdi23.pdf"}],"msr-author-ordering":[{"type":"text","value":"Inho Choi","user_id":0,"rest_url":false},{"type":"text","value":"Ellis Michael","user_id":0,"rest_url":false},{"type":"text","value":"Yunfan Li","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Dan Ports","user_id":37404,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Dan Ports"},{"type":"text","value":"Jialin Li","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144927],"msr_project":[617940],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":617940,"post_title":"Prometheus","post_name":"prometheus-microsoft-research","post_type":"msr-project","post_date":"2019-10-28 12:28:14","post_modified":"2022-04-21 15:55:10","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/prometheus-microsoft-research\/","post_excerpt":"Project Prometheus is building faster, more efficient datacenter systems by co-designing distributed systems with new network primitives. 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