Wireless sensor networks (WSNs) are evolving to support sense-and-react applications, where actuators are physically interspersed with the sensors that trigger them. This solution maximizes localized interactions, improving resource utilization and reducing latency w.r.t. solutions with a centralized sink. Nevertheless, application development becomes more complex: the control logic must be embedded in the network, and coordination among multiple tasks is needed to achieve the application goals. This paper presents TeenyLIME, a WSN middleware designed to address the above challenges. TeenyLIME provides programmers with the high-level abstraction of a tuple space, enabling data sharing among neighboring devices. These and other WSN-specific constructs simplify the development of a wide range of applications, including sense-and-react ones. TeenyLIME yields simpler, cleaner, and more reusable implementations, at the cost of only a very limited decrease in performance. We support these claims through a source-level, quantitative comparison between implementations based on TeenyLIME and on mainstream approaches, and by analyzing measures of processing overhead and power consumption obtained through cycle-accurate emulation.

Programming Wireless Sensor Networks with the TeenyLIME Middleware

MOTTOLA, LUCA;
2007-01-01

Abstract

Wireless sensor networks (WSNs) are evolving to support sense-and-react applications, where actuators are physically interspersed with the sensors that trigger them. This solution maximizes localized interactions, improving resource utilization and reducing latency w.r.t. solutions with a centralized sink. Nevertheless, application development becomes more complex: the control logic must be embedded in the network, and coordination among multiple tasks is needed to achieve the application goals. This paper presents TeenyLIME, a WSN middleware designed to address the above challenges. TeenyLIME provides programmers with the high-level abstraction of a tuple space, enabling data sharing among neighboring devices. These and other WSN-specific constructs simplify the development of a wide range of applications, including sense-and-react ones. TeenyLIME yields simpler, cleaner, and more reusable implementations, at the cost of only a very limited decrease in performance. We support these claims through a source-level, quantitative comparison between implementations based on TeenyLIME and on mainstream approaches, and by analyzing measures of processing overhead and power consumption obtained through cycle-accurate emulation.
8th ACM/IFIP/USENIX International Middleware Conference
3540767770
9783540767770
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/637926
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