{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T22:30:29Z","timestamp":1774909829149,"version":"3.50.1"},"reference-count":58,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2005,3,1]],"date-time":"2005-03-01T00:00:00Z","timestamp":1109635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Database Syst."],"published-print":{"date-parts":[[2005,3]]},"abstract":"<jats:p>\n            We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (\n            <jats:italic>sampled<\/jats:italic>\n            ) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices.\n          <\/jats:p>","DOI":"10.1145\/1061318.1061322","type":"journal-article","created":{"date-parts":[[2005,8,3]],"date-time":"2005-08-03T08:30:55Z","timestamp":1123057855000},"page":"122-173","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1314,"title":["TinyDB: an acquisitional query processing system for sensor networks"],"prefix":"10.1145","volume":"30","author":[{"given":"Samuel R.","family":"Madden","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA"}]},{"given":"Michael J.","family":"Franklin","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA"}]},{"given":"Joseph M.","family":"Hellerstein","sequence":"additional","affiliation":[{"name":"University of California, Berkeley, Berkeley, CA"}]},{"given":"Wei","family":"Hong","sequence":"additional","affiliation":[{"name":"Intel Research, Berkeley, CA"}]}],"member":"320","published-online":{"date-parts":[[2005,3]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the Workshop on Foundations of Models and Languages for Data and Objects. 1--17","author":"Alonso R.","unstructured":"Alonso , R. and Ganguly , S . 1993. Query optimization in mobile environments . In Proceedings of the Workshop on Foundations of Models and Languages for Data and Objects. 1--17 .]] Alonso, R. and Ganguly, S. 1993. Query optimization in mobile environments. In Proceedings of the Workshop on Foundations of Models and Languages for Data and Objects. 1--17.]]"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/170035.170092"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335420"},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of VLDB.]]","author":"Bancilhon F.","unstructured":"Bancilhon , F. , Briggs , T. , Khoshafian , S. , and Valduriez , P . 1987. FAD, a powerful and simple database language . In Proceedings of VLDB.]] Bancilhon, F., Briggs, T., Khoshafian, S., and Valduriez, P. 1987. FAD, a powerful and simple database language. 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