This work studies how visual analysis tasks based on feature extraction can be speeded up in the context of Visual Sensor Networks. The main catch is for the camera node to leverage the presence of neighboring sensor nodes and offload the task, thus parallelizing its execution. We propose two mathematical programming formulations for the optimal visual task offloading problem:
the first one targets the minimization of the overall task completion time while enforcing energy consumption constraints onto the nodes; the second maximizes the overall sensor network lifetime subject to a temporal constraint on the task completion time.The aforementioned formulations are used to characterize the achievable speed-up and consequent energy consumption in representative visual sensor network topologies.