Remote incremental linking for energy-efficient reprogramming of sensor networks

With sensor networks expected to be deployed for long periods of time, the ability to reprogram them remotely is necessary for providing new services, fixing bugs and enhancing applications and system software. Given the envisioned scales of future sensor network deployments, their restricted accessibility and the limited energy and computing resources of sensors, transmitting raw binary images is inefficient. We present a technique to minimize the cost of application evolution by remotely and incrementally linking updated modules at the base station and distributing deltas of the prelinked software modules. This paper provides details of our implementation, some preliminary results and surveys critical research issues in developing a comprehensive framework for reprogramming sensor networks.

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