{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T09:16:05Z","timestamp":1721812565391},"reference-count":20,"publisher":"Association for Computing Machinery (ACM)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,3]]},"abstract":"<jats:p>Huge amounts of data are being generated by sensing devices every day, recording the status of objects and the environment. Such observational data is widely used in scientific research. As the capabilities of sensors keep improving, the data produced are drastically expanding in precision and quantity, making it a write-intensive domain. Log-structured storage is capable of providing high write throughput, and hence is a natural choice for managing large-scale observational data.<\/jats:p>\n          <jats:p>\n            In this paper, we propose an approach to indexing and querying observational data in log-structured storage. Based on key traits of observational data, we design a novel index approach called the\n            <jats:italic>CR-index<\/jats:italic>\n            (Continuous Range Index), which provides fast query performance without compromising write throughput. It is a lightweight structure that is fast to construct and often small enough to reside in RAM. Our experimental results show that the\n            <jats:italic>CR-index<\/jats:italic>\n            is superior in handling observational data compared to other indexing techniques. While our focus is scientific data, we believe our index will be effective for other applications with similar properties, such as process monitoring in manufacturing.\n          <\/jats:p>","DOI":"10.14778\/2732286.2732290","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"529-540","source":"Crossref","is-referenced-by-count":11,"title":["Lightweight indexing of observational data in log-structured storage"],"prefix":"10.14778","volume":"7","author":[{"given":"Sheng","family":"Wang","sequence":"first","affiliation":[{"name":"National University of Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Maier","sequence":"additional","affiliation":[{"name":"Portland State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beng Chin","family":"Ooi","sequence":"additional","affiliation":[{"name":"National University of Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,3]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Apache HBase. http:\/\/hbase.apache.org.  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Technical report, MITRE, 2007."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/356770.356776"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/1370949"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1559845.1559934"},{"key":"e_1_2_1_13_1","first-page":"75","volume-title":"Proc of ISGC 2011 & OGF 31","volume":"1","author":"W. Ku and G. Center","year":"2011","unstructured":"W. Ku and G. Center . The cloud-based sensor data warehouse . In Proc of ISGC 2011 & OGF 31 , volume 1 , page 75 , 2011 . W. Ku and G. Center. The cloud-based sensor data warehouse. In Proc of ISGC 2011 & OGF 31, volume 1, page 75, 2011."},{"key":"e_1_2_1_14_1","volume-title":"TokuTek","author":"Kuszmaul B.","year":"2010","unstructured":"B. Kuszmaul . How tokudb fractal tree indexes work. Technical report , TokuTek , 2010 . B. Kuszmaul. How tokudb fractal tree indexes work. Technical report, TokuTek, 2010."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1773912.1773922"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/1920841.1920990"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s002360050048"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213862"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2013.6544876"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.14778\/2336664.2336673"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2732286.2732290","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T11:00:46Z","timestamp":1672225246000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2732286.2732290"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,3]]},"references-count":20,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2014,3]]}},"alternative-id":["10.14778\/2732286.2732290"],"URL":"https:\/\/doi.org\/10.14778\/2732286.2732290","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2014,3]]}}}