DocumentCode
1680843
Title
Optimizing Query Routing Trees in Wireless Sensor Networks
Author
Chatzimilioudis, Georgios ; Cuzzocrea, Alfredo ; Gunopulos, Dimitrios
Author_Institution
Comput. Sci. Dept., Univ. of California, Riverside, CA, USA
Volume
2
fYear
2010
Firstpage
315
Lastpage
322
Abstract
The focus of this work is to adaptively optimize continuous queries in a wireless sensor network. Therefore, we analyze and categorize the different types of queries used by wireless sensor applications. We present a short survey on the existing algorithms that can be adapted and used to optimize the different types of queries. We present their strengths and their drawbacks and identify that continuous subset queries can be further optimized. We propose a framework for answering continuous subset queries with multiple operators that can adapt to network and data changes. A query routing tree can be broken down into an operator tree, an operator placement assignment and a routing scheme. The operator tree defines the order in which the operators will be applied to the data and how the results will be pipelined from one operator to the other. The operator placement assignment defines on which node of the network each operator will be hosted and executed. We assume shortest-path routing and propose efficient methods to adapt operator placement and the operator tree dynamically for continuous queries. Our technique for adapting the actual operator tree is the first in literature to adapt the actual operator tree in a distributed fashion.
Keywords
query processing; telecommunication network routing; trees (mathematics); wireless sensor networks; continuous query; operator placement assignment; operator tree; optimizing query routing trees; routing scheme; shortest-path routing; subset query; wireless sensor applications; wireless sensor networks; Buildings; Energy consumption; Heuristic algorithms; Optimization; Query processing; Routing; Wireless sensor networks; adaptation; operator placement; query optimization; routing tree;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location
Arras
ISSN
1082-3409
Print_ISBN
978-1-4244-8817-9
Type
conf
DOI
10.1109/ICTAI.2010.117
Filename
5670090
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