TY - GEN
T1 - Adaptive working schedule for duty-cycle opportunistic mobile networks
AU - Zhou, Huan
AU - Zhao, Hongyang
AU - Liu, Chi Harold
AU - Chen, Jiming
PY - 2013
Y1 - 2013
N2 - 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, then propose an adaptive working schedule for duty-cycle OppNets. The proposed schedule uses the past recorded contact histories to predict the future contact information, so as 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 schedule. The results show that our proposed adaptive working schedule is superior to the random working schedule in terms of delivery ratio and delivery delay.
AB - 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, then propose an adaptive working schedule for duty-cycle OppNets. The proposed schedule uses the past recorded contact histories to predict the future contact information, so as 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 schedule. The results show that our proposed adaptive working schedule is superior to the random working schedule in terms of delivery ratio and delivery delay.
UR - http://www.scopus.com/inward/record.url?scp=84891362604&partnerID=8YFLogxK
U2 - 10.1109/ICC.2013.6654737
DO - 10.1109/ICC.2013.6654737
M3 - Conference contribution
AN - SCOPUS:84891362604
SN - 9781467331227
T3 - IEEE International Conference on Communications
SP - 1565
EP - 1569
BT - 2013 IEEE International Conference on Communications, ICC 2013
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2013 IEEE International Conference on Communications, ICC 2013
Y2 - 9 June 2013 through 13 June 2013
ER -