Adaptive working schedule for duty-cycle opportunistic mobile networks

In opportunistic mobile networks (OppNets), a large amount of energy is consumed by idle listening, instead of infrequent data exchange. This makes energy saving a challenging and fundamental problem in OppNets since nodes are typically battery powered. Asynchronous duty-cycle operation is a promising approach for energy saving in OppNets; however, if its working schedule is not effectively designed, it may also cause significant network performance degradation. Therefore, it is pressing to design an energy-efficient working schedule for duty-cycle OppNets. In this paper, we first analyze the contact process in duty-cycle OppNets and then propose an adaptive working schedule for duty-cycle OppNets. The proposed adaptive working schedule uses the past recorded contact histories to predict future contact information to adaptively configure the working schedule of each node in the network. Finally, extensive real trace-driven simulations are conducted to evaluate the performance of our proposed adaptive working schedule. Extensive real trace-driven simulation results demonstrate that our proposed adaptive working schedule is superior to the random working schedule and the periodical working schedule algorithms in terms of the number of effect contacts, delivery ratio, and delivery delay.