  We study energy management policies for the compression and transmission of
source data collected by an energy-harvesting sensor node with a finite energy
buffer (e.g., rechargeable battery) and a finite data buffer (memory) between
source encoder and channel encoder. The sensor node can adapt the source and
channel coding rates depending on the observation and channel states. In such a
system, the absence of precise information about the amount of energy available
in the future is a key challenge. We provide analytical bounds and scaling laws
for the average distortion that depend on the size of the energy and data
buffers. We furthermore design a resource allocation policy that achieves
almost optimal distortion scaling. Our results demonstrate that the energy
leakage of state of art energy management policies can be avoided by jointly
controlling the source and channel coding rates.
