A stream database server for sensor applications

We present a framework for stream data processing that incorporates a stream database server as a fundamental component. The server operates as the stream control interface between arrays of distributed data stream sources and end-user clients that access and analyze the streams. The underlying framework provides novel stream management and query processing mechanisms to support the online acquisition, management, storage, non-blocking query, and integration of data streams for distributed multi-sensor networks. In this paper, we define our stream model and stream representation for the stream database, and we describe the functionality and implementation of key components of the stream processing framework, including the query processing interface for source streams, the stream manager, the stream buffer manager, nonblocking query execution, and a new class of join algorithms for joining multiple data streams constrained by a sliding time window. We conduct experiments using real and synthetic data streams to evaluate the performance of the new algorithms against traditional stream join algorithms. The experiments show significant performance improvements and also demonstrate the flexibility of our system in handling data streams. A multi-sensor network application for the intelligent detection of hazardous materials is presented to illustrate the capabilities of our framework.