Tree-Adapting: an Adaptive Data Aggregation Method for Wireless Sensor Networks

Wireless technology enables the sensors to gather data to the base station through a so-called multi-hop communication. For data aggregation in wireless sensor networks, a tree overlay is necessary to guide the data transportation from one node to another in an efficient way. Here the data aggregation means that the data is merged while it is transported among the sensors. TinyDB and Cougar are typical data aggregation systems which make use of a tree overlay to do the data aggregation efficiently. However, the tree overlay used in those systems are not optimized for various kinds of data aggregation in response to various kinds of sensed data. Here the sensed data can be kinds of temperature, humidity, noise, etc. In this paper, we propose a new method, Tree-Adapting, to optimize the data aggregation by re-constructing adaptively a new aggregation tree in response to each series of sensed data.