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Jeong-Joon Kim 1 and In-Su Shin 1 and Yan-Sheng Zhang 2 and Dong-Oh Kim 3 and Ki-Joon Han 1
Recommended by Jianliang Xu
1, Division of Computer Science & Engineering, Konkuk University, Seoul 143-701, Republic of Korea
2, Division of Software Engineering, Northeastern University, Shenyang 110819, China
3, Cloud Computing Research Department, Electronics and Telecommunications Research Institute, Daejeon 305-700, Republic of Korea
Received 19 February 2012; Revised 25 May 2012; Accepted 25 June 2012
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
With the rapid advance of sensing technologies for capturing various types of data such as temperature, humidity, and pressure as well as the development of wireless communication technologies, research is being made actively for utilizing wireless sensor network technologies in diverse application areas including military, medicine, meteorology, environment, transportation, home, and business [ 1, 2].
Generally sensor nodes do not use unicasting (use ACK) whsen they regularly send the sensed data. Rather, they multicast or broadcast to the sensor nodes within the scope of the communication [ 3]. Also, sensor nodes basically know the content of the query that S-node (the starting node) sent, effective time of the query (from the reception of the query to the transmission of the first sensed data), and the cycle of the query (interval to transmit the sensed data).
In particular, the aggregate query process, which is to obtain aggregate results from data collected by sensors, is recognized as an important research area [ 4]. Aggregate queries execute functions such as MAX, MIN, SUM, AVG, COUNT, MEDIAN, and HISTOGRAM on the entire wireless sensor network or a specific region of the network.
Conventional centered aggregate query processing techniques have the problem of high energy consumption by the sensor nodes. Thus, in order to reduce the energy consumption of sensor nodes, aggregate query processing in network is being studied actively, which processes aggregate queries on sensed data in the sensor nodes and then sends the results to the server [ 5- 7]. Representative techniques of aggregate query processing in network include TAG (Tiny AGgregation) and IWQE (Itinerary-based Window Query Execution) that focus on routing...