Optimal Sensor Scheduling via Non-standard Multi-armed Bandit Formulation

This paper addresses optimal sensor scheduling for maximizing network lifetime. We formulate this problem as a nonstandard multi-armed bandit process with non-discounted reward and finite stopping time. We find that the optimal strategy should choose the sensor that has the largest Gittins’ index. Exploiting the underlying structure of sensor scheduling problem, we reduce the computational complex of the Gittins’ index from O(N) to O(N) with respect to the network size N . Moreover, we derive closed-form expression for the Gittins’ index. We also show that choosing the sensor with the most residual energy is an optimal strategy when the channel fading is independently and identically distributed across sensors.