Distributed Selection: A Missing Piece of Data Aggregation.
In this article, we study the problem of distributed selection from a theoretical point of view. Given a general connected graph of diameter D consisting of n nodes in which each node holds a numeric element, the goal of a k-selection algorithm is to determine the kth smallest of these elements. We...
| Published in: | Communications of the ACM Vol. 51; no. 9; pp. 93 - 100 |
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| Main Authors: | , , |
| Format: | Article |
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Association for Computing Machinery
Sep2008
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=34141234&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 34141234 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Sep2008 vid: 51 iid: 9 pid: 68 pub: Association for Computing Machinery artinfo: ui: 34141234 10.1145/1378727.1378749 ppf: 93 ppct: 7 formats: tig: atl: Distributed Selection: A Missing Piece of Data Aggregation. aug: au: Kuhn, Fabian Locher, Thomas Wattenhofer, Roger affil: Postdoc researcher, Institute of Theoretical Computer Science, ETH Zurich, Switzerland. Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland. Professor, Head of Distributed Computing Group, Computer Engineering and Networks Laboratory, ETH Zurich, Switzerland. su: Database management software Algorithms Aggregation operators Database design Management information systems Electronic data processing Computer software sug: subj: Database management software Algorithms Aggregation operators Database design Management information systems Electronic data processing Computer software ab: In this article, we study the problem of distributed selection from a theoretical point of view. Given a general connected graph of diameter D consisting of n nodes in which each node holds a numeric element, the goal of a k-selection algorithm is to determine the kth smallest of these elements. We prove that distributed selection indeed requires more work than other aggregation functions such as, e.g., the computation of the average or the maximum of all elements. On the other hand, we show that the kth smallest element can be computed efficiently by providing both a randomized and a deterministic k-selection algorithm, dispelling the misconception that solving distributed selection through in-network aggregation is infeasible. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2008 holdings: @attributes: islocal: N |
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