在雾云计算中的物联网应用程序的启发式任务调度方面的进展:挑战和前景
1Department of Computer Science and Artificial Intelligence, College of Computing, Umm Al-Qura University, Makkah, Makkah Almukaramah, Saudi Arabia.
PeerJ. Computer science
|July 10, 2024
概括
本综述探讨了雾计算 (FC) 中的任务调度,这是一个分布式计算范式. 它分析了各种调度方法,并提出了对高效,安全和可扩展的FC系统的未来研究.
科学领域:
- 计算机科学 计算机科学
- 分布式系统 分布式系统
- 人工智能的人工智能
背景情况:
- 雾计算 (FC) 将云计算功能扩展到网络边缘,解决物联网计算需求.
- 在FC中,有效的任务安排对于能源效率,资源优化和及时完成任务至关重要.
研究的目的:
- 综合审查雾计算系统任务调度方法的进展.
- 确定关键挑战,并为强大的FC任务安排提出未来研究方向.
主要方法:
- 对各种任务安排方法的系统文献分析:基于优先级的,贪的,元启发式的,基于学习的,混合的和以自然为灵感的.
- 识别和讨论包括动态环境,异质性,可扩展性,资源限制,安全性和透明度在内的挑战.
主要成果:
- 在雾计算的背景下,评估各种任务调度算法的优点和局限性.
- 识别阻碍当前FC任务调度解决方案的性能和采用的关键挑战.
结论:
- 未来的研究应该专注于整合机器学习,联合学习,资源意识算法,安全技术和可解释的AI.
- 解决这些研究方向将促进更强大,更适应,更安全,更可持续的雾计算系统.
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