In the rapidly developing field of sensor networks, bridging the gap between the applications and the hardware presents a major challenge. Although middleware is one solution, it must be specialized to the qualities of sensor networks, especially energy consumption. The work presented here provides two contributions: a new operational setting for sensor networks and a middleware for easing software development in this setting. The operational setting we target removes the usual assumption of a central collection point for sensor data. Instead the sensors are sparsely distributed in an environment, not necessarily able to communicate among themselves, and a set of clients move through space accessing the data of sensors nearby, yielding a system which naturally provides context relevant information to client applications. We further assume the clients are wirelessly networked and share locally accessed data. This scenario is relevant, for example, when relief workers access the information in their zone and share this information with other workers. Our second contribution, the middleware itself, is an extension of LIME, our earlier work on middleware for mobile ad hoc networks. The model makes sensor data available through a tuple space interface, providing the illusion of shared memory between applications and sensors. This paper presents both the model and the implementation of our middleware incorporated with the Crossbow Mote sensor platform.

TinyLime: Bridging Mobile and Sensor Networks through Middleware

Murphy, Amy Lynn;Picco, Gian Pietro
2005

Abstract

In the rapidly developing field of sensor networks, bridging the gap between the applications and the hardware presents a major challenge. Although middleware is one solution, it must be specialized to the qualities of sensor networks, especially energy consumption. The work presented here provides two contributions: a new operational setting for sensor networks and a middleware for easing software development in this setting. The operational setting we target removes the usual assumption of a central collection point for sensor data. Instead the sensors are sparsely distributed in an environment, not necessarily able to communicate among themselves, and a set of clients move through space accessing the data of sensors nearby, yielding a system which naturally provides context relevant information to client applications. We further assume the clients are wirelessly networked and share locally accessed data. This scenario is relevant, for example, when relief workers access the information in their zone and share this information with other workers. Our second contribution, the middleware itself, is an extension of LIME, our earlier work on middleware for mobile ad hoc networks. The model makes sensor data available through a tuple space interface, providing the illusion of shared memory between applications and sensors. This paper presents both the model and the implementation of our middleware incorporated with the Crossbow Mote sensor platform.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/76000
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