Research Article
Multi-objective Optimization for IoT Devices Association in Fog-Computing Based RAN
@INPROCEEDINGS{10.1007/978-3-030-14657-3_34, author={Hua Shi and Yinbin Feng and Ronghua Luo and Jie Zheng}, title={Multi-objective Optimization for IoT Devices Association in Fog-Computing Based RAN}, proceedings={IoT as a Service. 4th EAI International Conference, IoTaaS 2018, Xi’an, China, November 17--18, 2018, Proceedings}, proceedings_a={IOTAAS}, year={2019}, month={3}, keywords={Internet of Things Fog computing Device association Multi-objective optimization}, doi={10.1007/978-3-030-14657-3_34} }- Hua Shi
Yinbin Feng
Ronghua Luo
Jie Zheng
Year: 2019
Multi-objective Optimization for IoT Devices Association in Fog-Computing Based RAN
IOTAAS
Springer
DOI: 10.1007/978-3-030-14657-3_34
Abstract
The fog-computing based radio access network (F-RAN) is proposed in 5G systems facilitating the deployment of IoT, where fog-computing based access points (FAPs) provide both computational and radio resource closer to IoT devices (IoTDs). On one side, IoTDs try to associate with the FAPs to minimize the power consumption. On the other side, the concentration of IoTDs leads to the long execution delay which consists of transmission time and processing time, where we assume an equal share of computing resource for co-FAP IoTDs. As a result, we investigate multi-objective optimization (MOP) for IoTDs association in F-RAN considering both radio and computing resource. The objects involve minimizing the power consumption and the execution delay of IoTDs. Then we apply quantum-behaved particle swarm optimization with low complexity to solve the MOP. Simulation results show the proposed algorithm achieves a tradeoff between the two objects. It consumes a little more power consumption and brings a big improvement of the average execution delay.