Energy is a scarce resource on battery-powered wireless sensor nodes, and wireless communication represents the major consumer of electric energy on most current platforms. Reducing the number and size of radio transmissions thus represents a viable approach to save energy and extend a node's operational time. In the domain of pervasive computing, where a periodic reporting of data (e.g., a user's vital parameters) is often being used, packets cannot always be simply omitted from transmission. Even if the contained data have not changed, these periodically transmitted message double as beacons to indicate that the sensor node has not run out of energy. Hence, reducing the sizes of transmitted messages remains the only available solution to achieve energy savings in such sensor networks. In this paper, we show how precomputed codebooks can be used to encode messages in an energy-efficient way and thus reduce the size of the transmitted packets. We present how we extract these code mappings from real-world data, and describe how packets are encoded prior to their transmission in order to reduce the incurred energy demand. We practically assess the energy demand on TelosB nodes and prove that up to 17.2% of energy can be saved when our approach is applied.
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