电子学报

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智能环境下基于边缘设备规则推理的数据预部署研究

汪成亮1, 赵凯1, 刘嘉敏2   

  1. 1.重庆大学计算机学院,重庆 400044
    2.重庆大学光电工程学院,重庆 400044
  • 收稿日期:2020-08-15 修回日期:2021-10-08 出版日期:2022-07-04
  • 作者简介:汪成亮 男,1975年5月出生,四川资阳人.博士,现为重庆大学计算机学院教授,博士生导师.主要研究方向为复杂系统智能控制、无线网络及RFID研究与应用等.E-mail: wangcl@cqu.edu.cn
    赵 凯 男,1995年10月出生,湖北潜江人.重庆大学在读硕士研究生.主要研究方向为智能环境、物联网.E-mail: 20144732@cqu.edu.cn
  • 基金资助:
    国家自然科学基金(61672115);重庆市技术创新与应用发展专项重大主题专项(cstc2019jscx-zdztzxX0037)

Study on Data Pre-deployment Based on Inference and Computing of Edge Devices in Smart Environment

WANG Cheng-liang1, ZHAO Kai1, Liu Jia-min2   

  1. 1.College of Computer Science and Technology,Chongqing University,Chongqing 400044,China
    2.College of Optoelectronic Engineering,Chongqing University,Chongqing 400044,China
  • Received:2020-08-15 Revised:2021-10-08 Online:2022-07-04

摘要:

在现有的规则推理机制下,大量的传感器数据导致的过大规则匹配期间的实时特征计算量降低了推理实时性,同时边缘设备受限的内存资源难以应对如此庞大的数据量.为此,本文设计了数据预部署方案(Data Pre-Deployment Scheme,DPDS).利用规则解析与预处理模块解析规则集得到的规则网络和轻量级特征表(Light-weight Characteristic Table,LCT),该方案通过引用LCT中的值而无需进行实时特征计算使推理效率和实时性得到显著提高,并大大降低了规则匹配期间的内存占用量.通过实验,我们发现即使在规则、数据规模很大的情况下,DPDS仍然具有较高的时间效率和空间效率.

关键词: 智能环境, 边缘设备, 规则推理, 规则匹配, 无线传感器网络

Abstract:

Under the existing rule inference mechanism, the amount of real-time feature calculation during rule matching caused by a large amount of sensor data reduces the inference real-time performance. At the same time, the limited memory resources of edge devices cannot cope with such a huge amount of data. For this reason, this thesis designs the Data Pre-Deployment Scheme(DPDS). By utilizing the rule network and Light-weight Characteristic Table(LCT) obtained by the rule analysis and preprocessing module, This scheme enables the rule network to directly reference the characteristic values in the LCT during inference without real-time feature calculations, which significantly improves efficiency and real-time and greatly reduces the memory usage of the inference process. The experimental results show that even in the case of a large amount of data and rules, DPDS still has high time efficiency and space efficiency.

Key words: smart environment, edge device, rule inference, rule matching, wireless sensor network

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