%0 Journal Article
%T Continuous Distributed Top-k Monitoring over Data Streams<br>多数据流上的连续分布式Top-k监测
%A DENG Bo
%A RAO Xiang
%A JIA Yan
%A YANG Shu-Qiang
%A <br>邓波
%A 饶翔
%A 贾焰
%A 杨树强
%J 计算机科学
%D 2007
%I 
%X Monitoring data streams in a distributed system is the focus of much research in recent years.This paper addresses the generic and efficient processing of distributed top-k monitoring,which is continuously reporting the k largest values according to a user-specified ranking function over distributed multiple data streams.In practice,the user-specified ranking function would be arbitrary ranking function.Unfortunately,state-of-art distributed top-k monitoring approaches only support the sum function as the ranking function.In this paper,we present a general algorithm GMR for distributed top-k monitoring,which supports arbitrary continuous and strict monotone aggregation functions.The communication cost of GMR is independent of k.We verify the effectiveness of GMR empirically using both real-world and synthetic data sets.We show that GMR reduces overall communication cost by an order of magnitude compared with alternatives.
%K GMR
%K Distributed
%K Top-k
%K Data streams
%K Monitoring<br>GMR
%K 分布式
%K Top-k
%K 数据流
%K 监测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=4087221266F172B805CFFC2481EF94B2&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=0B39A22176CE99FB&sid=F122871CC7EC92DC&eid=1F199509C0B6C4D6&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=22