{"id":161018,"date":"2011-06-30T00:00:00","date_gmt":"2011-06-30T07:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/managing-cost-performance-and-reliability-tradeoffs-for-energy-aware-server-provisioning\/"},"modified":"2018-10-16T21:04:54","modified_gmt":"2018-10-17T04:04:54","slug":"managing-cost-performance-and-reliability-tradeoffs-for-energy-aware-server-provisioning","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/managing-cost-performance-and-reliability-tradeoffs-for-energy-aware-server-provisioning\/","title":{"rendered":"Managing Cost, Performance, and Reliability Tradeoffs for Energy-Aware Server Provisioning"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We present ACES, an automated server provisioning system that aims to meet workload demand while minimizing energy consumption in data centers. To perform energy-aware server provisioning, ACES faces three key tradeoffs between cost, performance, and reliability: (1) maximizing energy savings vs. minimizing unmet load demand, (2) managing low power draw vs. high transition latencies for multiple power management schemes, and (3) balancing energy savings vs. reliability costs\u00a0of server components due to on-off cycles. To address these challenges, ACES (1) predicts demand in the near future to turn on servers gradually before they are needed and avoids turning on unnecessary servers to cope with transient load\u00a0spikes, (2) formulates an optimization problem that minimizes a linear combination of unmet demand and total energy and reliability costs, and uses the program structure to solve the problem ef\ufb01ciently in practice, and (3) constructs an execution\u00a0plan based on the optimization decisions to transition servers between different power states and actuates them using system and load management interfaces. Our evaluation on three data center workloads shows that ACES\u2019s energy savings are close to\u00a0the optimal and it delivers power proportionality while balancing the tradeoff between energy savings and reliability costs.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present ACES, an automated server provisioning system that aims to meet workload demand while minimizing energy consumption in data centers. To perform energy-aware server provisioning, ACES faces three key tradeoffs between cost, performance, and reliability: (1) maximizing energy savings vs. minimizing unmet load demand, (2) managing low power draw vs. high transition latencies for [&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":[{"type":"user_nicename","value":"bguenter","user_id":"31216"},{"type":"user_nicename","value":"navendu","user_id":"33061"},{"type":"user_nicename","value":"cjwill","user_id":"31448"}],"msr_publishername":"IEEE Communications Society","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"30th IEEE International Conference on Computer Communications (INFOCOM)","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":"30th IEEE International Conference on Computer Communications (INFOCOM)","msr_doi":"10.1109\/INFCOM.2011.5934917","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":"2011-06-30","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"http:\/\/ieeexplore.ieee.org\/document\/5934917\/","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":2011,"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":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-161018","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"IEEE Communications Society","msr_edition":"30th IEEE International Conference on Computer Communications (INFOCOM)","msr_affiliation":"","msr_published_date":"2011-06-30","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":"348473","msr_publicationurl":"http:\/\/ieeexplore.ieee.org\/document\/5934917\/","msr_doi":"10.1109\/INFCOM.2011.5934917","msr_publication_uploader":[{"type":"file","title":"guenter11managing","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2011\/06\/guenter11managing.pdf","id":348473,"label_id":0},{"type":"url","title":"http:\/\/ieeexplore.ieee.org\/document\/5934917\/","viewUrl":false,"id":false,"label_id":0},{"type":"doi","title":"10.1109\/INFCOM.2011.5934917","viewUrl":false,"id":false,"label_id":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":0,"url":"http:\/\/ieeexplore.ieee.org\/document\/5934917\/"}],"msr-author-ordering":[{"type":"user_nicename","value":"bguenter","user_id":31216,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=bguenter"},{"type":"user_nicename","value":"navendu","user_id":33061,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=navendu"},{"type":"user_nicename","value":"cjwill","user_id":31448,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=cjwill"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[368936],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":368936,"post_title":"Linear Programming for Optimal Power Control of Data Center Computers","post_name":"linear-programming-for-optimal-power-control-of-data-center-computers","post_type":"msr-project","post_date":"2017-03-03 17:18:24","post_modified":"2020-03-13 17:31:40","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/linear-programming-for-optimal-power-control-of-data-center-computers\/","post_excerpt":"An algorithm which breaks the problem into two pieces: predicting future demand and determining power state transitions to minimize power while meeting demand in the best way.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/368936"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/161018","targetHints":{"allow":["GET"]}}],"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":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/161018\/revisions"}],"predecessor-version":[{"id":532669,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/161018\/revisions\/532669"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=161018"}],"wp:term":[{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=161018"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=161018"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=161018"},{"taxonomy":"msr-publisher","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publisher?post=161018"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=161018"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=161018"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=161018"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=161018"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=161018"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=161018"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=161018"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=161018"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}