多区域,多服务和多层边缘云连续性规划
Anargyros J Roumeliotis1, Efstratios Myritzis1, Evangelos Kosmatos1
1Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, GR-157 80 Athens, Greece.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
边缘云环境的最佳规划需要有效地部署计算连续资源. 基于批次的任务处理为复杂的计算需求提供了更快,更可扩展的解决方案.
科学领域:
- 计算机科学 计算机科学
- 分布式系统 分布式系统
- 边缘计算 边缘计算
背景情况:
- 边缘云环境越来越复杂,需要高效的资源管理.
- 优化规划对于满足各种处理,速度和延迟需求至关重要.
- 现有的线下规划方法可能会与现实世界的问题大小作斗争.
研究的目的:
- 研究多区域,多服务,多层边缘云系统的最佳规划策略.
- 评估部署计算连续性的不同方法 (处理设备及其分配).
- 分析各种规划方案的性能和执行时间之间的权衡.
主要方法:
- 三种离线计算连续性规划方案的比较:一个处理一次所有任务,两个使用代任务分批处理.
- 直接复杂的分析与更简单,更快的规划方法.
- 调查任务选择策略,包括随机选择和聚类方法,用于基于组的方法.
主要成果:
- 同时处理所有任务可以提供更好的性能,但执行时间更长.
- 代的,以批量为导向的方案提供了更快的方法,并且对于更大的问题更具可扩展性.
- 在以小组为基础的计划中随机选择任务通常会比其他策略产生更好的表现.
结论:
- 批量导向的计算连续规划对于大规模的边缘云环境是有效的.
- 任务选择策略的选择显著影响了基于小组的计划的表现.
- 随机任务选择成为优化这些系统性能的一种强有力的策略.
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