Academic
Publications
OMSI-Tree: Power-Awareness Query Processing over Sensor Networks by Removing Overlapping Regions

OMSI-Tree: Power-Awareness Query Processing over Sensor Networks by Removing Overlapping Regions,10.1007/978-3-540-72909-9_21,Wei Zha,Sang-Hun Eo,Byeo

OMSI-Tree: Power-Awareness Query Processing over Sensor Networks by Removing Overlapping Regions  
BibTex | RIS | RefWorks Download
Sensor networks have played an important role in our daily life. The most common applications are light and humidity monitoring, environment and habitat monitoring. Window queries over the sensor networks become popular. However, due to the limited power supply, ordinary query methods can not be applied on sensor networks. Queries over sensor networks should be power-aware to guarantee the maximum power savings. In this paper, we concentrate on minimal power consumption by avoiding the expensive communication. A lot of work have been done to reduce the participated nodes, but none of them have considered the overlapping minimum bounded rectangle (MBR) of sensors which make them impossible to reach the optimization solution. The OMSI-tree and OMR algorithm proposed by us can efficiently solve this problem by executing a given query only on the sensors involved. Experiments show that there is an obvious improvement compared with TinyDB and other spatial index, adopting the proposed schema and algorithm.
Conference: Asia-Pacific Web Conference - APWeb , pp. 204-210, 2007
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.