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Though there are a variety of Distributed Stream Processing Systems (DSPSs) that facilitate the development of streaming applications, resource management and task scheduling is not automatically handled by the DSPS middleware and requires a laborious process to tune toward specific deployment targets. As the advent of cloud computing has supported renting resources on-demand, it is of great interest to review the research progress of hosting streaming systems in clouds under certain Service Level Agreements (SLA) and cost constraints. In this article, we introduce the hierarchical structure of streaming systems, define the scope of the resource management problem, and present a comprehensive taxonomy in this context covering critical research topics such as resource provisioning, operator parallelisation, and task scheduling. The literature is then reviewed following the taxonomy structure, facilitating a deeper understanding of the research landscape through classification and comparison of existing works. Finally, we discuss the open issues and future research directions toward realising an automatic, SLA-aware resource management framework.<\/jats:p>","DOI":"10.1145\/3355399","type":"journal-article","created":{"date-parts":[[2020,5,29]],"date-time":"2020-05-29T04:28:26Z","timestamp":1590726506000},"page":"1-41","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":64,"title":["Resource Management and Scheduling in Distributed Stream Processing Systems"],"prefix":"10.1145","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0998-2034","authenticated-orcid":false,"given":"Xunyun","family":"Liu","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Center, National Innovation Institute of Defense Technology, Beijing, China"}]},{"given":"Rajkumar","family":"Buyya","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Parkville, VIC, Australia"}]}],"member":"320","published-online":{"date-parts":[[2020,5,28]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1921029"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2010.172"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2528412"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488222.2488267"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1932682.1869469"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2169090.2169091"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488222.2488258"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2009.5160874"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.parco.2010.09.005"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3127479.3127492"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/SRDS.2012.55"},{"key":"e_1_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-75178-8_2"},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2017.2723403"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDEW.2007.4401049"},{"key":"e_1_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.190686"},{"key":"e_1_2_2_16_1","first-page":"28","article-title":"Apache Flink: Unified stream and batch processing in a single engine","volume":"36","author":"Carbone Paris","year":"2015","unstructured":"Paris Carbone , Stephan Ewen , Seif Haridi , Asterios Katsifodimos , Volker Markl , and Kostas Tzoumas . 2015 . 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