{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:11:36Z","timestamp":1750306296328,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2016,7,25]],"date-time":"2016-07-25T00:00:00Z","timestamp":1469404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSF CNS","award":["1319527"],"award-info":[{"award-number":["1319527"]}]},{"name":"NSF CCF","award":["0964471"],"award-info":[{"award-number":["0964471"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2016,7,25]]},"DOI":"10.1145\/2955193.2955206","type":"proceedings-article","created":{"date-parts":[[2016,7,15]],"date-time":"2016-07-15T14:36:21Z","timestamp":1468593381000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["New techniques to curtail the tail latency in stream processing systems"],"prefix":"10.1145","author":[{"given":"Guangxiang","family":"Du","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Indranil","family":"Gupta","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Urbana, IL"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2016,7,25]]},"reference":[{"volume-title":"https:\/\/flink.apache.org\/","year":"2016","key":"e_1_3_2_1_1_1","unstructured":"Apache Flink. https:\/\/flink.apache.org\/ , 2016 . Apache Flink. https:\/\/flink.apache.org\/, 2016."},{"volume-title":"http:\/\/spark.apache.org\/","year":"2016","key":"e_1_3_2_1_2_1","unstructured":"Apache Spark. http:\/\/spark.apache.org\/ , 2016 . Apache Spark. http:\/\/spark.apache.org\/, 2016."},{"volume-title":"http:\/\/storm.apache.org\/","year":"2016","key":"e_1_3_2_1_3_1","unstructured":"Apache Storm. http:\/\/storm.apache.org\/ , 2016 . Apache Storm. http:\/\/storm.apache.org\/, 2016."},{"volume-title":"https:\/\/cloud.google.com\/compute\/","year":"2016","key":"e_1_3_2_1_4_1","unstructured":"Google Compute Engine. https:\/\/cloud.google.com\/compute\/ , 2016 . Google Compute Engine. https:\/\/cloud.google.com\/compute\/, 2016."},{"volume-title":"https:\/\/en.wikipedia.org\/wiki\/M\/M\/c_queue\/","year":"2016","key":"e_1_3_2_1_5_1","unstructured":"M\/M\/c queue. https:\/\/en.wikipedia.org\/wiki\/M\/M\/c_queue\/ , 2016 . M\/M\/c queue. https:\/\/en.wikipedia.org\/wiki\/M\/M\/c_queue\/, 2016."},{"volume-title":"http:\/\/samza.apache.org\/","year":"2016","key":"e_1_3_2_1_6_1","unstructured":"Samza. http:\/\/samza.apache.org\/ , 2016 . Samza. http:\/\/samza.apache.org\/, 2016."},{"key":"e_1_3_2_1_7_1","first-page":"19","volume-title":"Proc. USENIX NSDI","author":"Alizadeh M.","year":"2012","unstructured":"M. Alizadeh Less is More: Trading a Little Bandwidth for Ultra-low Latency in the Data Center . In Proc. USENIX NSDI , pages 19 -- 19 , 2012 . M. Alizadeh et al. Less is More: Trading a Little Bandwidth for Ultra-low Latency in the Data Center. In Proc. USENIX NSDI, pages 19--19, 2012."},{"key":"e_1_3_2_1_8_1","first-page":"265","volume-title":"Proc. USENIX OSDI","author":"Ananthanarayanan G.","year":"2010","unstructured":"G. Ananthanarayanan Reining in the Outliers in Map-reduce Clusters Using Mantri . In Proc. USENIX OSDI , pages 265 -- 278 , 2010 . G. Ananthanarayanan et al. Reining in the Outliers in Map-reduce Clusters Using Mantri. In Proc. USENIX OSDI, pages 265--278, 2010."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488222.2488267"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/324133.324234"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2612669.2612701"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2408776.2408794"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"G. Du. \"New Techniques to Lower Tail Latency in Stream Processing Systems\" MS Thesis UIUC 2016. http:\/\/dprg.cs.uiuc.edu\/docs\/Guangxiang_thesis\/DU-THESIS-2016.pdf.  G. Du. \"New Techniques to Lower Tail Latency in Stream Processing Systems\" MS Thesis UIUC 2016. http:\/\/dprg.cs.uiuc.edu\/docs\/Guangxiang_thesis\/DU-THESIS-2016.pdf.","DOI":"10.1145\/2955193.2955206"},{"key":"e_1_3_2_1_15_1","first-page":"411","volume-title":"Proc. IEEE ICDCS","author":"T. Z.","year":"2015","unstructured":"T. Z. J. Fu et al. DRS: Dynamic Resource Scheduling for Real-Time Analytics over Fast Streams . In Proc. IEEE ICDCS , pages 411 -- 420 , 2015 . T. Z. J. Fu et al. DRS: Dynamic Resource Scheduling for Real-Time Analytics over Fast Streams. In Proc. IEEE ICDCS, pages 411--420, 2015."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7363751"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2600428.2609572"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742788"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2670979.2670988"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/71.963420"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732939.2732944"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2009.5161036"},{"key":"e_1_3_2_1_23_1","first-page":"513","volume-title":"Proc. USENIX NSDI","author":"Suresh L.","year":"2015","unstructured":"L. Suresh : Cutting Tail Latency in Cloud Data Stores via Adaptive Replica Selection . In Proc. USENIX NSDI , pages 513 -- 527 , 2015 . L. Suresh et al. C3: Cutting Tail Latency in Cloud Data Stores via Adaptive Replica Selection. In Proc. USENIX NSDI, pages 513--527, 2015."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2535372.2535392"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2014.61"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/IC2E.2016.38"},{"key":"e_1_3_2_1_27_1","first-page":"10","volume-title":"Proc. USENIX HotCloud","author":"Zaharia M.","year":"2012","unstructured":"M. Zaharia : An efficient and fault-tolerant model for stream processing on large clusters . In Proc. USENIX HotCloud , pages 10 -- 10 , 2012 . M. Zaharia et al. Discretized streams: An efficient and fault-tolerant model for stream processing on large clusters. In Proc. USENIX HotCloud, pages 10--10, 2012."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2670979.2671008"}],"event":{"name":"PODC '16: ACM Symposium on Principles of Distributed Computing","acronym":"PODC '16","location":"Chicago Illinois"},"container-title":["Proceedings of the 4th Workshop on Distributed Cloud Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2955193.2955206","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2955193.2955206","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:39:11Z","timestamp":1750221551000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2955193.2955206"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,25]]},"references-count":28,"alternative-id":["10.1145\/2955193.2955206","10.1145\/2955193"],"URL":"https:\/\/doi.org\/10.1145\/2955193.2955206","relation":{},"subject":[],"published":{"date-parts":[[2016,7,25]]},"assertion":[{"value":"2016-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}