在异质网络中优化能源分配,使用最小-最大和局部约束来支持环境智能
Alessandro Aloisio1, Domenico D Bloisi1, Marco Romano1
1Department of International Humanities and Social Sciences, University of International Studies of Rome (UNINT), 00147 Rome, Italy.
Sensors (Basel, Switzerland)
|May 14, 2025
概括
本研究介绍了物联网 (IoT) 中环境智能 (AmI) 系统的新型多界面网络方法. 它通过平衡能源效率和连接性来优化无线网络性能并延长设备寿命.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 无处不在的计算 无处不在的计算
背景情况:
- 环境智能 (AmI) 系统通过创建适应性环境来提高用户的舒适性和效率.
- 物联网 (IoT) 框架,利用传感器和执行器,对于AMI系统运行至关重要.
- 强大的无线网络对于将各种设备集成到AmI/IoT生态系统中至关重要,但在协议兼容性,电源和计算方面面临挑战.
研究的目的:
- 在物联网生态系统中设计用于AMI系统的异质无线网络,使用一种新的多接口网络方法.
- 通过选择适当的通信协议 (例如Wi-Fi,蓝牙,5G) 来优化电池驱动设备的能源效率.
- 通过平衡功耗和效率来提高整体网络性能和延长运营寿命.
主要方法:
- 在多界面网络中开发一种新型号,专门用于降低电池消耗和最大限度地提高AMI系统性能.
- 分析与拟议模型相关的计算复杂性.
- 基于固定参数可处理性理论的两个解决方案算法的建议,用于特定的网络类.
主要成果:
- 对于多界面网络的一种新型模型,可以有效降低AmI/IoT系统中的电池消耗.
- 通过优化界面选择,证明了网络性能的提高.
- 识别计算复杂性和开发可处理的算法,用于实际实施.
结论:
- 拟议的多界面网络方法为增强物联网中的AMI系统提供了可行的解决方案.
- 优化通信接口选择对于能源效率和网络寿命至关重要.
- 开发的算法提供了在现实世界中部署此类网络的高效方法.
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