Abstract
Recent advances in computing technology have led to the production of a new class of computing device: the wireless, battery powered, smart sensor. Traditional sensors deployed throughout buildings, labs, and equipment are passive devices that simply modulate a voltage based on some environmental parameter. In contrast, these new sensors are active, full fledged computers, capable not only of sampling real world phenomena but also filtering, sharing, and combining those sensor readings with each other and nearby Internet-equipped endpoints. Over the past several years, we have designed and implemented a query processor for such sensor networks called TinyDB. TinyDB is a distributed query processor that runs on each of the nodes in a sensor network that is explicitly designed to simplify many of the data collection applications described above. TinyDB runs on the Berkeley mote platform, on top of the TinyOS operating system. TinyDB has many of the features of a traditional query processor (e.g. the ability to select, join, project, and aggregate data), but also incorporates a number of other optimization features designed to minimize power consumption. In this chapter, we review of many of the features of TinyDB and other sensor network query processing systems. We also discuss how TinyDB interfaces with a data stream management system (DSMS), examples of which are discussed elsewhere in this book.
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Abadi, D., Madden, S., Lindner, W. (2016). Sensor Network Integration with Streaming Database Systems. In: Garofalakis, M., Gehrke, J., Rastogi, R. (eds) Data Stream Management. Data-Centric Systems and Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28608-0_20
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DOI: https://doi.org/10.1007/978-3-540-28608-0_20
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