Distortion Minimization In Energy Harvesting Sensor Nodes With Compression Power Constraints

We consider the design of energy management policies for multimedia wireless sensor nodes that rely entirely on harvesting energy from the environment for both the data acquisition and transmission. In many high volume data sensing applications, the sampled data is compressed before transmission to meet the bandwidth and transmit power constraints. The compression results in data distortion, but it reduces the amount of data to be transmitted. As a consequence, the transmission energy is reduced, but excessive compression may consume more energy than what is saved by transmitting less data. This points to a trade-off between compression and transmission (in terms of both the energy and time allocated to these operations). Our goal is to identify the optimal energy management policies that minimize the long-term average distortion at the receiver. We first study the optimal solution in an off-line setting and then propose three on-line policies. We highlight the importance of the compression power, showing that, all other system parameters being equal, the average distortion decreases exponentially as the compression power is increased by processing at a faster rate.