tailieunhanh - Towards Sensor Database Systems

Our infrastructure (Akash1 ) consists of a virtual storage system prototype designed to run on commodity hard- ware. It supports data accesses to multiple virtual vol- umes for any storage client, such as, database servers and file systems. It uses the Network Block Device (NBD) driver packaged with Linux to read and write log- ical blocks from the virtual storage system, as shown in Figure 3. NBD is a standard storage access proto- col similar to iSCSI, supported by Linux. It provides a method to communicate with a storage server over the network. The client machine (shown in left) mounts the virtual volume as a NBD device (., /dev/nbd1) which is used by. | Towards Sensor Database Systems Philippe Bonnet Johannes Gehrke Praveen Seshadri1 Computer Science Department Upson Hall Cornell University Ithaca NY 14853 UsA bonnet j ohannes praveen @ Abstract. Sensor networks are being widely deployed for measurement detection and surveillance applications. In these new applications users issue long-running queries over a combination of stored data and sensor data. Most existing applications rely on a centralized system for collecting sensor data. These systems lack flexibility because data is extracted in a predefined way also they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system queries dictate which data is extracted from the sensors. In this paper we define a model for sensor databases. Stored data are represented as relations while sensor data are represented as time series. Each long-running query formulated over a sensor database defines a persistent view which is maintained during a given time interval. We also describe the design and implementation of the COUGAR sensor database system. 1 Introduction The widespread deployment of sensors is transforming the physical world into a computing platform. Modern sensors not only respond to physical signals to produce data they also embed computing and communication capabilities. They are thus able to store process locally and transfer the data they produce. Still at the heart of each sensor a set of signal processing functions transform physical signals such as heat light sound pressure magnetism or a particular motion into sensor data . measurements of physical phenomena as well as detection classification or tracking of physical objects. Applications monitor the physical world by querying and analyzing sensor data. Examples of monitoring applications include supervising items in a factory warehouse gathering information in a .