一个增强的鱼优化算法用于边缘计算环境中的任务调度
Li Han1, Shuaijie Zhu1, Haoyang Zhao1
1College of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou, China.
Frontiers in big data
|November 14, 2024
概括
增强的鱼优化算法 (EWOA) 优化了边缘计算中的任务调度,降低了成本和完成时间,同时改善了对要求高的应用程序的资源利用率.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 分布式计算 (Distributed Computing) 是一种分布式计算.
背景情况:
- 移动设备和计算密集型应用程序产生大量数据,压迫边缘计算资源.
- 边缘环境中的实时任务执行面临着由于资源有限和要求高的应用程序的挑战.
研究的目的:
- 提出一个增强的鱼优化算法 (EWOA),用于边缘计算中的高效任务调度.
- 开发一个优化CPU,内存,时间和资源利用的多目标模型.
主要方法:
- 开发了边缘计算的多目标任务调度模型.
- 将模型转化为鱼优化问题,使用混乱映射来进行种群初始化和非线性收因子来搜索平衡.
- 在实验边缘计算环境中对ODTS,WOA,HWACO和CATSA进行了EWOA性能评估.
主要成果:
- EWOA将运营成本降低了29.22%.
- EWOA将任务完成时间减少了17.04%.
- 通过EWOA,节点资源利用率提高了9.5%.
结论:
- EWOA在边缘计算任务调度的成本,时间和资源利用方面取得了显著的改进.
- 限制包括不考虑网络延迟和用户流动性.
- 未来的工作将探索耐故障调度,以满足动态用户需求和提高服务质量.
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