Reprogramming over the network is an essential requirement in large-scale, long term wireless sensor network deployments. In this paper, we present LACONIC, a history-based code dissemination technique, for programmable wireless sensor networks supporting multiple applications. In order to attain network traffic abatement and timely code delivery, LACONIC exploits (1) application calling history and (2) code dissemination history. The application calling history is modeled by a Application Call Graph(ACG) which represents the calling relationships among multiple applications. Second, the code dissemination history as a set of observed previous code forwarding paths indicates previous code forwarding path of the associated application in the context of the application calling history. Therefore, the code request triggered by a requester is reached to the responder by traveling along the path, not being consecutively flooded. Using a flooding-based existing code dissemination work as the baseline, we show the effectiveness of Laconic in terms of network traffic and time delay through both probability model-based analysis and simulation results.

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This paper proposes a sensor data compression mechanism based on the amount of change of sensor input data and a power management scheme for various sensors used for the motion recognition application. The experimental results confirmed that the proposed compression mechanism and power management scheme reduced the wakeup count of the sensor hub core and the amount of data transmitted to the core by about 78% compared to the conventional data buffering structure, and the power consumption of the IMU (inertial measurement unit) is reduced by about 56%.

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