TY - GEN
T1 - Joint multi-user resource scheduling and computation offloading in small cell networks
AU - Labidi, Wael
AU - Sarkiss, Mireille
AU - Kamoun, Mohamed
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/4
Y1 - 2015/12/4
N2 - In this paper, we address computation offloading problem from mobile users to their serving small cell base stations. These base stations can be endowed with some computational capabilities providing thus users proximity access to the cloud services. We aim to jointly optimize the radio resource scheduling and computation offloading in order to minimize the average energy consumed by all the users terminals to process their mobile applications under average delay constraints tolerated by these applications. We investigate for this problem offline and online dynamic programming approaches and we devise deterministic solutions to find the optimal scheduling-offloading policy. The proposed solutions select only one user for scheduling, hence offloading, and decides for the other users either local processing or staying idle according to their application rates. We show that the offline strategy is optimal in terms of energy saving compared to the online strategy. It can benefit from prior knowledge on the channel statistics and the application properties to satisfy the users requirements.
AB - In this paper, we address computation offloading problem from mobile users to their serving small cell base stations. These base stations can be endowed with some computational capabilities providing thus users proximity access to the cloud services. We aim to jointly optimize the radio resource scheduling and computation offloading in order to minimize the average energy consumed by all the users terminals to process their mobile applications under average delay constraints tolerated by these applications. We investigate for this problem offline and online dynamic programming approaches and we devise deterministic solutions to find the optimal scheduling-offloading policy. The proposed solutions select only one user for scheduling, hence offloading, and decides for the other users either local processing or staying idle according to their application rates. We show that the offline strategy is optimal in terms of energy saving compared to the online strategy. It can benefit from prior knowledge on the channel statistics and the application properties to satisfy the users requirements.
U2 - 10.1109/WiMOB.2015.7348043
DO - 10.1109/WiMOB.2015.7348043
M3 - Conference contribution
AN - SCOPUS:84964301250
T3 - 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2015
SP - 794
EP - 801
BT - 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2015
Y2 - 19 October 2015 through 21 October 2015
ER -