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LLM4ETS: Self-Evolving Algorithm Design for Edge Task Scheduling via Large Language Models

delete2026-09-29
delete0
PRE
AI
Y
Yuqi Zhao
S
Shendong Gao
Y
Yatong Wang
Y
Yutao Ma *
李
李冰 (Bing Li)
J
Jian Wang
B
Boris Sedlak
P
Praveen Kumar Donta
S
Schahram Dustdar
DOI：10.1002/spe.70110delete
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摘要

摘要

En 中文
随着5G和物联网的迅速普及，确保边缘计算中的低延迟对于实时处理应用已成为关键。然而，现有的任务调度方法通常因手动参数调整和向最优性能收敛缓慢而难以有效平衡多个优化目标。
Keyword:
edge computing
evolutionary computing
large language models
self-evolving
task scheduling

期刊

S
SOFTWARE-PRACTICE & EXPERIENCE
IF:
2.7
论文数:
46
被引数:
0

机构

C
central china normal university
学者数:
355
论文数: 119
被引数: 0
S
Stockholm University
学者数:
215
论文数: 112
被引数: 0
W
wuhan university
学者数:
2.3K
论文数: 680
被引数: 0
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