Data aggregation for low power wireless devices

Kevin Schubert, Nicholas Bambos

Abstract: We propose a framework that evaluates data aggregation schemes for wireless protocols with an application emphasis on low power devices and the 802.15.4 protocol. A stochastic wireless model of the interference environment for Internet of Things (IoT) devices, is combined with the power budget of a modern wireless system on a chip to determine the sensitivity to and advantages of data aggregation. We then use the wireless model as the basis of heuristic technique that trades off device power use and data delays to develop optimizing transmission schemes. We compare our heuristically derived scheme with other simple transmission schemes. It is shown that the use of our data aggregation strategy can significantly reduce device power usage and system resources such as channel accesses.