Machine-learning-based parallel genetic algorithms for multi-objective optimization in ultra-reliable low-latency WSNs
Different from conventional wireless sensor networks (WSNs), ultra-reliable and low-latency WSNs (uRLLWSNs), being an important application of 5G networks, must meet more stringent performance requirements. In this paper, we propose a novel algorithm to improve uRLLWSNs’ performance by applying mach...
| Main Authors: | , , , , |
|---|---|
| 其他作者: | |
| 格式: | Journal Article |
| 語言: | English |
| 出版: |
2019
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/104803 http://hdl.handle.net/10220/48646 |