数据采样和传输减少的多代理预测方法,用于物联网传感器网络中的物联网传感器网络
1Institute of Computer Science, University of Silesia, Będzińska 39, 41-200 Sosnowiec, Poland.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
本研究介绍了一种用于物联网 (IoT) 传感器网络的新方法,以减少数据传输. 通过预测传感器读数间隔,它有效地抑制不必要的数据,为低端设备节省资源.
科学领域:
- 计算机科学 计算机科学
- 电气工程 电气工程
- 数据科学数据科学数据科学
背景情况:
- 传感器网络对于物联网 (IoT) 应用至关重要,提供实时数据.
- 网络带宽,存储,处理和能源有限,需要在物联网传感器网络中高效处理数据.
研究的目的:
- 引入一种新的方法来减少物联网传感器网络中的数据传输.
- 通过预测传感器读取间隔来减少传感器节点收集的数据样本的数量.
主要方法:
- 采用多代理系统来确定可能的传感器读数的预测间隔.
- 代理人独立分析历史数据,以评估过去和当前传感器读数之间的相似性,以进行预测.
- 预测算法在物联网网关或云端执行.
主要成果:
- 该方法有效地抑制了不必要的传输,并减少了收集的数据样本.
- 实验结果表明,预测间隔的准确性有所提高.
- 与现有的预测方法相比,实现了更高的传输减少率.
结论:
- 拟议的方法适用于资源有限的物联网传感器网络,低端设备.
- 它通过确定传感数据的有用性和优化传输频率来有效地管理数据.
- 这种方法提高了预测准确性,并大大减少了物联网传感器网络中的数据传输.
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