使用智能接入点系统进行节能AP选择,以增加物联网设备的寿命
Seungjin Lee1, Jaeeun Park2, Hyungwoo Choi2
1Institute for IT Convergence, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
本研究引入了一种新的强化学习方法,用于物联网 (IoT) 设备选择接入点 (AP),显著提高能源效率并减少拥挤网络中的延迟.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 电信 电信服务 电信服务 电信服务
背景情况:
- 物联网 (IoT) 设备在拥挤的环境中面临能源消耗挑战.
- 无线网络中的碰撞导致数据包转发,增加能源使用和延迟.
- 现有的接入点 (AP) 选择方案没有充分解决能源效率和负载平衡问题.
研究的目的:
- 为物联网设备开发一种新的节能AP选择方案.
- 为了减轻由偏向的AP连接引起的不平衡负载问题.
- 在能源消耗和延迟方面提高物联网设备的整体性能.
主要方法:
- 为AP选择提出了一个能源和延迟强化学习 (EL-RL) 模型.
- 分析了Wi-Fi网络中的碰撞概率,以最大限度地减少转发.
- 将平均能耗和平均延迟集成到AP选择过程中.
主要成果:
- 在能源效率方面取得了最大53%的改进.
- 降低了高达50%的上链延迟.
- 与传统方法相比,将物联网设备的预期寿命延长了2.1倍.
结论:
- 该EL-RL模型有效地提高了能源效率,并减少了物联网设备的延迟时间.
- 拟议的方案比传统的AP选择方法提供了显著的改进.
- 这种方法对于优化物联网设备在密集网络环境中的性能至关重要.
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