Paper Info
Title
Semantic load shedding for prioritized continuous queries over data streams
Abstract
A data stream management system (DSMS) has to handle high-volume and bursty data streams with large number of continuous queries. When an input rate of any data stream exceeds the system capacity, the DSMS has to shed load by dropping some fraction of unprocessed data items. In this paper, we propose a new load shedding algorithm for continuous queries over data streams. Unlike previous algorithms assuming that all queries are equally important, we consider the priority of each query so that more important queries make more convincing outputs. As a result, the proposed algorithm can support differentiated quality of services by exploiting semantics inherent to applications. We also report the experiment results confirming the benefits of the proposed algorithm.
Year
DOI
Venue
2005
10.1007/11569596_83
ISCIS
Keywords
Field
DocType
data stream management system,bursty data stream,continuous query,system capacity,prioritized continuous query,important query,semantic load,previous algorithm,unprocessed data item,proposed algorithm,new load,data stream,quality of service
Data stream management system,Data stream mining,Data transmission,Shared memory,Computer science,Data stream,Virtual memory,Quality of service,Semantics,Distributed computing
Conference
Volume
ISSN
ISBN
3733
0302-9743
3-540-29414-7
Citations 
PageRank 
References 
0
0.34
10
Authors
2
Name
Order
Citations
PageRank
Jaeseok Park1196.05
Haengrae Cho23814.71