  Any properly designed network coding technique can result in increased
throughput and reliability of multi-hop wireless networks by taking advantage
of the broadcast nature of wireless medium. In many inter-flow network coding
schemes nodes are encouraged to overhear neighbours traffic in order to improve
coding opportunities at the transmitter nodes. A study of these schemes reveal
that some of the overheard packets are not useful for coding operation and thus
this forced overhearing increases energy consumption dramatically. In this
paper, we formulate network coding aware sleep/wakeup scheduling as a semi
Markov decision process (SMDP) that leads to an optimal node operation. In the
proposed solution for SMDP, the network nodes learn when to switch off their
transceiver in order to conserve energy and when to stay awake to overhear some
useful packets. One of the main challenges here is the delay in obtaining
reward signals by nodes. We employ a modified Reinforcement Learning (RL)
method based on continuous-time Q-learning to overcome this challenge in the
learning process. Our simulation results confirm the optimality of the new
methodology.
