Research Article
Mobile Edge Computing-Enabled Resource Allocation for Ultra-Reliable and Low-Latency Communications
@INPROCEEDINGS{10.1007/978-3-030-32388-2_30, author={Yun Yu and Siyuan Zhou and Xiaocan Lian and Guoping Tan and Yingchi Mao}, title={Mobile Edge Computing-Enabled Resource Allocation for Ultra-Reliable and Low-Latency Communications}, proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings}, proceedings_a={MLICOM}, year={2019}, month={10}, keywords={Mobile edge computing Resource allocation Probability constraints Ultra reliable and low latency (URLLC) Stochastic network optimization}, doi={10.1007/978-3-030-32388-2_30} }- Yun Yu
Siyuan Zhou
Xiaocan Lian
Guoping Tan
Yingchi Mao
Year: 2019
Mobile Edge Computing-Enabled Resource Allocation for Ultra-Reliable and Low-Latency Communications
MLICOM
Springer
DOI: 10.1007/978-3-030-32388-2_30
Abstract
Mission critical services and applications with computation-intensive tasks require extremely low latency, while task offloading for mobile edge computing (MEC) incurs extra latency. In this work, the optimization of power consumption and delay are studied under ultra reliable and low latency (URLLC) framework in a multiuser MEC scenario. Delay and reliability are relying on users’ task queue lengths, which is attested by probabilistic constraints. Different from the current literature, we consider a comprehensive system model taking into account the effects of bandwidth, computation capability, and transmit power. By introducing the approach of Lyapunov stochastic optimization, the problem is solved by splitting the multi-objective optimization problem into three single optimization problems. Performance analysis is conducted for the proposed algorithm, which illustrates that the tradeoff parameter indicates the tradeoff between power and delay. Simulation results are presented to validate the theoretical analysis of the impact of various parameters and demonstrate the effectiveness of the proposed approach.
