Research Article
Energy-Efficient Resource Allocation for Mobile Edge Computing System Supporting Multiple Mobile Devices
@INPROCEEDINGS{10.1007/978-3-030-44751-9_19, author={Song Jin and Qi Gu and Xiang Li and Xuming An and Rongfei Fan}, title={Energy-Efficient Resource Allocation for Mobile Edge Computing System Supporting Multiple Mobile Devices}, proceedings={IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings}, proceedings_a={IOTAAS}, year={2020}, month={6}, keywords={Edge computing Data offloading Multiple users FDMA}, doi={10.1007/978-3-030-44751-9_19} }- Song Jin
Qi Gu
Xiang Li
Xuming An
Rongfei Fan
Year: 2020
Energy-Efficient Resource Allocation for Mobile Edge Computing System Supporting Multiple Mobile Devices
IOTAAS
Springer
DOI: 10.1007/978-3-030-44751-9_19
Abstract
Nowadays, mobile edge computing (MEC) has become a promising technique to provide mobile devices with intensive computation capability for the applications in the Internet of Things and 5G communications. In a MEC system, a mobile device, who has computation tasks to complete, would like to offload part or all the data for computation to a MEC server, due to the limit of local computation capability. In this paper, we consider a MEC system with one MEC server and multiple mobile devices, who access into the MEC server via frequency division multiple access (FDMA). The energy consumption of all the mobile devices is targeted to minimized via optimizing the computation and communication resources, including the amount of data for offloading, the bandwidth for accessing, the energy budget for offloading data, the time budget for offloading, for each mobile device. An optimization problem is formulated, which is non-convex. We decompose it into two levels. In the lower level, a convex optimization problems is formulated. In the upper level, a one-dimensional variable is to be optimized by bisection search method.