{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:17:46Z","timestamp":1781104666856,"version":"3.54.1"},"reference-count":0,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2001,10,1]]},"abstract":"<p>An adaptive probe-based optimization technique is developed and demonstrated in the context of an Internet-based distributed database environment. More and more common are database systems, which are distributed across servers communicating via the Internet where a query at a given site might require data from remote sites. Optimizing the response time of such queries is a challenging task due to the unpredictability of server performance and network traffic at the time of data shipment; this may result in the selection of an expensive query plan using a static query optimizer. We constructed an experimental setup consisting of two servers running the same DBMS connected via the Internet. Concentrating on join queries, we demonstrate how a static query optimizer might choose an expensive plan by mistake. This is due to the lack of a priori knowledge of the run-time environment, inaccurate statistical assumptions in size estimation, and neglecting the cost of remote method invocation. These shortcomings are addressed collectively by proposing a probing mechanism. Furthermore, we extend our mechanism with an adaptive technique that detects sub-optimality of a plan during query execution and attempts to switch to the cheapest plan while avoiding redundant work and imposing little overhead. An implementation of our run-time optimization technique for join queries was constructed in the Java language and incorporated into an experimental setup. The results demonstrate the superiority of our probe-based optimization over a static optimization.<\/p>","DOI":"10.4018\/jdm.2001100101","type":"journal-article","created":{"date-parts":[[2011,2,15]],"date-time":"2011-02-15T14:13:22Z","timestamp":1297779202000},"page":"3-14","source":"Crossref","is-referenced-by-count":3,"title":["An Adaptive Probe-Based Technique to Optimize Join Queries in Distributed Internet Databases"],"prefix":"10.4018","volume":"12","author":[{"given":"Latifur","family":"Khan","sequence":"first","affiliation":[{"name":"University of Texas-Dallas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dennis","family":"McLeod","sequence":"additional","affiliation":[{"name":"University of Southern California-Los Angeles, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cyrus","family":"Shahabi","sequence":"additional","affiliation":[{"name":"University of Southern California-Los Angeles, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","container-title":["Journal of Database Management"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=3268","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,2]],"date-time":"2022-06-02T00:35:16Z","timestamp":1654130116000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jdm.2001100101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2001,10,1]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2001,10]]}},"URL":"https:\/\/doi.org\/10.4018\/jdm.2001100101","relation":{},"ISSN":["1063-8016","1533-8010"],"issn-type":[{"value":"1063-8016","type":"print"},{"value":"1533-8010","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,10,1]]}}}