高效的情境感知计算:在情境感知计算中的动态工作内存更新的系统模型.
Mumtaz Ali1, Muhammad Arshad1, Ijaz Uddin1
1Department of Computer Science, City University of Science and Information Technology, Peshawar, Pakistan.
PeerJ. Computer science
|July 10, 2024
概括
本研究引入了一种新的方法,用于资源有限的设备中的动态工作记忆管理. 它优化了智能上下文感知计算系统的内存使用情况.
科学领域:
- 计算机科学 计算机科学
- 无处不在的计算 无处不在的计算
- 人工智能的人工智能
背景情况:
- 智能设备的扩散使得无处不在的计算成为可能,在环境中提供智能服务.
- 移动和可穿戴设备上的上下文感知系统在内存管理方面面临挑战.
- 基于规则的推理是一种常见的方法,但在有效控制工作记忆方面存在困难.
研究的目的:
- 为了解决存储器受限设备中的动态工作记忆挑战.
- 引入一个系统的方法来删除内容以优化内存的利用.
- 为资源有限的环境增强智能系统的开发.
主要方法:
- 开发一种系统的方法来从工作记忆中动态删除内容.
- 在资源有限的设备上实施和评估方法.
- 专注于基于规则的推理系统在上下文意识的计算.
主要成果:
- 在资源有限的系统中证明了更好的内存利用.
- 展示了系统删除内容方法的有效性.
- 在移动和可穿戴设备上促进了更有效的上下文感知计算.
结论:
- 拟议的方法有效地管理受约束设备中的动态工作内存.
- 优化内存管理对于可穿戴设备上的先进智能系统至关重要.
- 这项工作通过高效的资源利用来推进上下文感知计算.
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