Energy-aware and robust task (re)assignment in embedded smart camera networks

Multi-camera multi-object tracking problem can be regarded as a multi-player game by adopting a game theoretical approach. In embedded vision sensor networks, energy, processing power and bandwidth are limited, and should be efficiently used. In this paper, in addition to dynamic grouping of the camera nodes, we focus on the (re)assignment of object tracking tasks by simultaneously considering energy levels, processing loads and accuracy/reliability of nodes in utility calculation. Instead of using a predetermined period to perform auctions, nodes trigger the reassignment process in an event-driven manner. Four scenarios are used for triggering reassignment, namely (i) new-object entry, (ii) object lost or exit, (iii) critical energy level or energy decrease rate, and (iv) critical target location and resolution. We also analyze the communication cost in terms of the number of messages sent between the cameras. We have performed experiments with different number of cameras and targets, and varying target trajectories and camera topology. We have computed the lifetime of the network with and without consideration of the energy levels in the task (re)assignment. We have also compared the number of messages sent with periodic reassignment and with the proposed event-driven triggering mechanism. The simulation results show a significant increase in the lifetime of the network as well as a decrease in the number of messages that are sent when the proposed approach is employed.