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Conference Paper
Cooperative Evolutionary Computation for Multi-RAT Edge Computing
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- Authors
- Zhao-Kun Shao, Kangyu Gao, Gyeong-June Hahm, Kyung-Yul Cheon, Hyenyeon Kwon, Seungkeun Park, Changjun Zhou, Zhonglong Zheng, Sang-Woon Jeon
- Issue Date
- 2025-06
- Citation
- Vehicular Technology Conference (VTC) 2025 (Spring), pp.1-6
- Language
- English
- Type
- Conference Paper
- Abstract
- Multi-radio access technology (multi-RAT) enabled mobile edge computing (MEC) has emerged as a promising paradigm for supporting heterogeneous applications. However, efficiently managing resources for both ultra-reliable low-latency communications (URLLC) and enhanced mobile broadband (eMBB) services in large-scale networks remains challenging. In this paper, we investigate a joint optimization problem involving user association and bandwidth allocation in multi-RAT-enabled MEC systems. We propose a novel cooperative evolutionary framework operated based on the interplay between inner and outer agents to efficiently optimize large-scale networks. Extensive simulation results demonstrate that the proposed approach significantly outperforms the conventional single-RAT MEC system and several representative evolutionary computation algorithms.
- KSP Keywords
- Access technology, Evolutionary Computation algorithms, Evolutionary framework, Heterogeneous Applications, Joint optimization, Mobile Broadband, Mobile Edge Computing(MEC), Multi-radio access, Multiple radio access technologies(Multi-RATs), Optimization problem, Radio Access Technologies(RATs)