{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:21:02Z","timestamp":1750220462355,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T00:00:00Z","timestamp":1628812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,13]]},"DOI":"10.1145\/3481646.3481660","type":"proceedings-article","created":{"date-parts":[[2021,11,26]],"date-time":"2021-11-26T23:06:13Z","timestamp":1637967973000},"page":"88-94","source":"Crossref","is-referenced-by-count":0,"title":["Component Profiling and Prediction Models for QoS-Aware Self-Adapting DSMS Framework"],"prefix":"10.1145","author":[{"given":"Tarjana","family":"Yagnik","sequence":"first","affiliation":[{"name":"De Montfort University, UK"}]},{"given":"Feng","family":"Chen","sequence":"additional","affiliation":[{"name":"De Montfort University, UK"}]},{"given":"Laleh","family":"Kasraian","sequence":"additional","affiliation":[{"name":"De Montfort University, UK"}]}],"member":"320","published-online":{"date-parts":[[2021,11,26]]},"reference":[{"first-page":"1634","volume-title":"Proceedings of the VLDB Endowment","author":"Noghabi S.A.","key":"e_1_3_2_1_1_1"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"[2]Gorawski M. Gorawska A. and Pasterak K. 2014. A survey of data stream processing tools. In Information sciences and systems 2014 (pp. 295-303). Springer Cham.  [2]Gorawski M. Gorawska A. and Pasterak K. 2014. A survey of data stream processing tools. In Information sciences and systems 2014 (pp. 295-303). Springer Cham.","DOI":"10.1007\/978-3-319-09465-6_31"},{"volume-title":"Proceedings of the 18th International Database Engineering & Applications Symposium (pp. 356-361)","author":"Liu X.","key":"e_1_3_2_1_3_1"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/141484.130333"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"[5]Pratama M. Ashfahani A. Ong Y.S. Ramasamy S. and Lughofer E. 2018. Autonomous deep learning: Incremental learning of denoising autoencoder for evolving data streams arXiv preprint arXiv:1809.09081.  [5]Pratama M. Ashfahani A. Ong Y.S. Ramasamy S. and Lughofer E. 2018. Autonomous deep learning: Incremental learning of denoising autoencoder for evolving data streams arXiv preprint arXiv:1809.09081.","DOI":"10.1109\/ICDMW.2019.00023"},{"key":"e_1_3_2_1_6_1","unstructured":"[6]Akidau T. 2015. The world beyond batch: Streaming 101. A High-Level Tour of Modern Data-Processing Concepts. Blog entry.  [6]Akidau T. 2015. The world beyond batch: Streaming 101. A High-Level Tour of Modern Data-Processing Concepts. Blog entry."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2946884"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2751606"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"[9]Iqbal M.H. and Soomro T.R. 2015. Big data analysis: Apache storm perspective. International journal of computer trends and technology 19(1) pp.9-14.  [9]Iqbal M.H. and Soomro T.R. 2015. Big data analysis: Apache storm perspective. International journal of computer trends and technology 19(1) pp.9-14.","DOI":"10.14445\/22312803\/IJCTT-V19P103"},{"volume-title":"2012 Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (pp. 58-65)","author":"Chauhan J.","key":"e_1_3_2_1_10_1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137765.3137770"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2751606"},{"volume-title":"Proceedings of ANZIIS\u201994-Australian New Zealnd Intelligent Information Systems Conference (pp. 357-361)","author":"Holmes G.","key":"e_1_3_2_1_13_1"},{"volume-title":"Proceedings of the 2005 ACM Symposium on Applied computing (pp. 573-577)","author":"Gama J.","key":"e_1_3_2_1_14_1"},{"volume-title":"International Symposium on Intelligent Data Analysis (pp. 249-260)","author":"Bifet A.","key":"e_1_3_2_1_15_1"},{"first-page":"686","volume-title":"International journal of computer science and management research, 1(4)","author":"Kabakchieva D.","key":"e_1_3_2_1_16_1"},{"volume-title":"Meta-sgd: Learning to learn quickly for few-shot learning. arXiv preprint arXiv:1707.09835.","year":"2017","author":"Li Z.","key":"e_1_3_2_1_17_1"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.02.004"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2016.2597546"},{"first-page":"344","volume-title":"2006 27th IEEE International Real-Time Systems Symposium (RTSS\u201906)","author":"Wei Y.","key":"e_1_3_2_1_20_1"},{"volume-title":"British National Conference on Databases (pp. 16-30)","author":"Jiang Q.","key":"e_1_3_2_1_21_1"},{"volume-title":"International Conference on Big Data Analytics (pp. 42-61)","author":"Gupta R.","key":"e_1_3_2_1_22_1"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"[\n  23\n  ]  Baru C. and Rabl T. 2016. Application-level benchmarking of big data systems. In Big Data Analytics (pp. 189-199). Springer New Delhi.  [23] Baru C. and Rabl T. 2016. Application-level benchmarking of big data systems. In Big Data Analytics (pp. 189-199). Springer New Delhi.","DOI":"10.1007\/978-81-322-3628-3_10"},{"volume-title":"2015 IEEE\/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (pp. 35-45)","author":"Nikravesh A.Y.","key":"e_1_3_2_1_24_1"},{"key":"e_1_3_2_1_25_1","unstructured":"[\n  25\n  ]  Yagnik T. Chen F. and Kasraian L. 2021 18 April. QoS-Aware Self-Adapting Resource Utilisation Framework For Distributed Stream Management Systems. In ALLDATA 2021 The Seventh International Conference on Big Data Small Data Linked Data and Open Data Porto Portugal. IARIA 2021 (pp. 1-9)  [25] Yagnik T. Chen F. and Kasraian L. 2021 18 April. QoS-Aware Self-Adapting Resource Utilisation Framework For Distributed Stream Management Systems. In ALLDATA 2021 The Seventh International Conference on Big Data Small Data Linked Data and Open Data Porto Portugal. IARIA 2021 (pp. 1-9)"}],"event":{"name":"ICCBDC 2021: 2021 5th International Conference on Cloud and Big Data Computing","acronym":"ICCBDC 2021","location":"Liverpool United Kingdom"},"container-title":["2021 5th International Conference on Cloud and Big Data Computing (ICCBDC)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3481646.3481660","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3481646.3481660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:13Z","timestamp":1750193293000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3481646.3481660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,13]]},"references-count":25,"alternative-id":["10.1145\/3481646.3481660","10.1145\/3481646"],"URL":"https:\/\/doi.org\/10.1145\/3481646.3481660","relation":{},"subject":[],"published":{"date-parts":[[2021,8,13]]}}}