| Abstract: | Detection of an environmental phenomenon, e.g. air pollution and oil spills, occurs when a group of sensors continuously produces similar readings (i.e. data streams) over a period of time. Thus, detection of environmental phenomena is basically a process of clustering the sensors' data streams, which commonly involves the processing of hundreds and maybe thousands of data streams in real time. Since the sensor network environment is wireless, energy conservation of the sensors would be the main concern. Thus in this paper, we propose an efficient and energy friendly distributed scheme to detect phenomena in a wireless sensor network (WSN). To achieve fast response, the proposed algorithms reduce the dimensionality of the streams. Then, each stream is represented by a point in a multi-dimensional grid. The algorithm uses a grid-based clustering technique to detect clusters of similar stream values. The processing of the algorithm is distributed among different elements of the WSN in a hierarchical topology for more energy efficiency. The paper shows the feasibility of the proposed fully distributed scheme by comparing it with three other WSN schemes in terms of clustering accuracy and energy consumption. |
