TY - GEN
T1 - Energy-Efficient Resource Allocation for Mobile Edge Computing System Supporting Multiple Mobile Devices
AU - Jin, Song
AU - Gu, Qi
AU - Li, Xiang
AU - An, Xuming
AU - Fan, Rongfei
N1 - Publisher Copyright:
© 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Data offloading
KW - Edge computing
KW - FDMA
KW - Multiple users
UR - http://www.scopus.com/inward/record.url?scp=85083971361&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-44751-9_19
DO - 10.1007/978-3-030-44751-9_19
M3 - Conference contribution
AN - SCOPUS:85083971361
SN - 9783030447502
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 228
EP - 234
BT - IoT as a Service - 5th EAI International Conference, IoTaaS 2019, Proceedings
A2 - Li, Bo
A2 - Yang, Mao
A2 - Yan, Zhongjiang
A2 - Zheng, Jie
A2 - Fang, Yong
PB - Springer
T2 - 5th EAI International Conference on IoT as a Service, IoTaaS 2019
Y2 - 16 November 2019 through 17 November 2019
ER -