1. OL-EUA: Online User Allocation for NOMA-Based Mobile Edge Computing
- Author
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Guangming Cui, Qiang He, Feifei Chen, Hai Jin, Fang Dong, Xiaoyu Xia, and Yun Yang
- Subjects
Mobile edge computing ,Computer Networks and Communications ,Computer science ,business.industry ,Transmitter power output ,medicine.disease ,Noma ,Server ,Cellular network ,medicine ,Key (cryptography) ,Enhanced Data Rates for GSM Evolution ,Electrical and Electronic Engineering ,business ,Software ,5G ,Computer network - Abstract
In recent years, mobile edge computing (MEC), as a key technology that facilitates the 5G mobile network, has raised a number of new challenges for app vendors, including the Edge User Allocation (EUA) problem. EUA aims to allocate as many app users as possible in an MEC system to minimum edge servers in the system. In non-orthogonal multiple access (NOMA)-based MEC system, multiple app users can be allocated to the same subchannel on an edge server through transmit power allocation based on their intra-cell and inter-cell interference. However, allocating excessive app users to the same subchannel may result in severe interference and consequently impact app users data rates. In addition, in an MEC system, app users join and depart randomly, and thus need to be allocated in an online manner. Existing EUA approaches suffer from poor performance in dynamic real-world NOMA-based MEC systems because they allocate app users in an offline manner and do not consider the complication caused by NOMA. In this paper, we propose OL-EUA, an online approach for solving dynamic EUA problem in NOMA-based MEC systems. Its performance is theoretically analyzed and experimentally evaluated against a baseline approach and two state-of-the-art approaches on a widely-used real-world dataset.
- Published
- 2023
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