{"64666":{"#nid":"64666","#data":{"type":"event","title":"No Need for Guesswork: Traffic-oblivious Resource Management  Policies for Multi-server systems","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE:\u003C\/strong\u003E\u0026nbsp; No Need for Guesswork: Traffic-oblivious Resource Management Policies for Multi-server systems\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER:\u003C\/strong\u003E\u0026nbsp; Varun Gupta, Faculty Candidate\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EWill it snow next week? Who will the next Super Bowl? Will my call center receive more than ten thousand calls tomorrow?\u003Cbr \/\u003E\u003Cbr \/\u003EUncertainty in traffic demand significantly impacts the operations decisions of multi-server systems (e.g., call centers, data centers, cloud platforms). For example, 1. Load Balancing: How should the load be distributed among a collection of heterogeneous servers? Should a request be dispatched to an idle slow server, or should it wait for a busy fast server?\u003Cbr \/\u003E2. Capacity Provisioning: How many servers should be commissioned to meet the demand? When should more servers be commissioned? When should existing servers be decommissioned to avoid waste?\u003Cbr \/\u003E\u003Cbr \/\u003EWhile demand forecasting is the de facto approach to overcome uncertainty, we ask: Are there simple load balancing and capacity provisioning policies that work well without predicting the traffic demand? By obviating the need for traffic analysis, not only are such policies simpler to deploy, they are also robust to forecasting errors. In the talk, I will present traffic-oblivious load balancing and capacity provisioning policies that answer the above questions affirmatively.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cbr \/\u003E\u003C\/strong\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"No Need for Guesswork: Traffic-oblivious Resource Management  Policies for Multi-server systems"}],"uid":"27187","created_gmt":"2011-02-28 13:56:21","changed_gmt":"2016-10-08 01:54:22","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2011-03-10T10:00:00-05:00","event_time_end":"2011-03-10T11:00:00-05:00","event_time_end_last":"2011-03-10T11:00:00-05:00","gmt_time_start":"2011-03-10 15:00:00","gmt_time_end":"2011-03-10 16:00:00","gmt_time_end_last":"2011-03-10 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}