2 research outputs found
An Adaptable IoT Rule Engine Framework for Dataflow Monitoring and Control Strategies
The monitoring of data generated by a large number of devices in Internet of
Things (IoT) systems is an important and complex issue. Several studies have
explored the use of generic rule engine, primarily based on the RETE algorithm,
for monitoring the flow of device data. In order to solve the performance
problem of the RETE algorithm in IoT scenarios, some studies have also proposed
improved RETE algorithms. However, implementing modifications to the general
rule engine remains challenges in practical applications. The Thingsboard
open-source platform introduces an IoT-specific rule engine that does not rely
on the RETE algorithm. Its interactive mode attracted attention from developers
and researchers. However, the close integration between its rule module and the
platform, as well as the difficulty in formulating rules for multiple devices,
limits its flexibility. This paper presents an adaptable and user-friendly rule
engine framework for monitoring and control IoT device data flows. The
framework is easily extensible and allows for the formulation of rules contain
multiple devices. We designed a Domain-Specific Language (DSL) for rule
description. A prototype system of this framework was implemented to verify the
validity of theoretical method. The framework has potential to be adaptable to
a wide range of IoT scenarios and is especially effective in where real-time
control demands are not as strict.Comment: 15 pages,10 figure