TY - GEN
T1 - Power-Optimal Scheduling for Delay Constrained Mobile Computation Offloading
AU - Han, Di
AU - Chen, Wei
AU - Fang, Yuguang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2018/7/27
Y1 - 2018/7/27
N2 - In this paper, we aim to obtain the optimal tradeoff among average delay, and average transmission and computation power consumptions in a mobile computation offloading system. A probabilistic approach is developed to jointly determine the transmission and computation rate in each time-slot. We model the queue lengths in the mobile device and computation resource with a two- dimensional Markov chain. Based on this model, we obtain the average delay and power consumption. Then, we formulate a joint queues aware optimization problem to minimize the average power consumption of the mobile device given constraints on average delay of tasks and average power consumption of the computation resource. By converting the problem into a linear programming, we obtain the optimal power-delay tradeoff and power-optimal Joint Transmission and Computing Scheduling (JTCS) strategy. Finally, the optimization results are validated by extensive simulations.
AB - In this paper, we aim to obtain the optimal tradeoff among average delay, and average transmission and computation power consumptions in a mobile computation offloading system. A probabilistic approach is developed to jointly determine the transmission and computation rate in each time-slot. We model the queue lengths in the mobile device and computation resource with a two- dimensional Markov chain. Based on this model, we obtain the average delay and power consumption. Then, we formulate a joint queues aware optimization problem to minimize the average power consumption of the mobile device given constraints on average delay of tasks and average power consumption of the computation resource. By converting the problem into a linear programming, we obtain the optimal power-delay tradeoff and power-optimal Joint Transmission and Computing Scheduling (JTCS) strategy. Finally, the optimization results are validated by extensive simulations.
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U2 - 10.1109/ICC.2018.8422686
DO - 10.1109/ICC.2018.8422686
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781538631805
VL - 2018-May
T3 - IEEE International Conference on Communications
BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PB - IEEE
T2 - 2018 IEEE International Conference on Communications, ICC 2018
Y2 - 20 May 2018 through 24 May 2018
ER -