To monitor skylines over dynamic data, one needs to continuously update the skyline query results in order to reflect the new data values. This paper tackles the problem of continuous skyline monitoring on a central query server over dynamic data from multiple data sites. Simply sending the updates of tuple values to the server is cost-prohibitive. Therefore, we propose an approach where the central server collaborates with the data sites to monitor the possible skyline changes. By doing so, the processing load is distributed over all the nodes instead of only on the central server. Furthermore, the approach can minimize the bandwidth consumption between the server and the data sites, which is often critical in a widely distributed environment. Extensive experiments demonstrate that our proposal is efficient and effective.
|Status||Udgivet - 2010|
|Begivenhed||22nd International Conference on Scientific and Statistical Database Management - Heidelberg, Tyskland|
Varighed: 30. jun. 2010 → 2. jul. 2010
Konferencens nummer: 22
|Konference||22nd International Conference on Scientific and Statistical Database Management|
|Periode||30/06/2010 → 02/07/2010|
|Sponsor||Heidelberg University , Heidelberg Institute for Theoretical Studies (HITS)|