Internet of Things Smart Rules Engine

Kargin, Anatolii; Petrenko, Tetyana

doi:10.1109/infocommst.2018.8632027

Cited by 11 publications

(1 citation statement)

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“…Another related piece of research is [ 13 ], where the authors proposed a rule engine which allowed flexible rule strategies. In terms of smart rules engines, in [ 14 , 15 ], the authors presented a solution based on fuzzy logic for processing information. The research presented in the current paper uses the rule engine from [ 16 ], mainly due to its simplicity.…”

Section: Related Workmentioning

confidence: 99%

Parallel Processing of Sensor Data in a Distributed Rules Engine Environment through Clustering and Data Flow Reconfiguration

Alexandrescu

2023

Sensors

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An emerging reality is the development of smart buildings and cities, which improve residents’ comfort. These environments employ multiple sensor networks, whose data must be acquired and processed in real time by multiple rule engines, which trigger events that enable specific actuators. The problem is how to handle those data in a scalable manner by using multiple processing instances to maximize the system throughput. This paper considers the types of sensors that are used in these scenarios and proposes a model for abstracting the information flow as a weighted dependency graph. Two parallel computing methods are then proposed for obtaining an efficient data flow: a variation of the parallel k-means clustering algorithm and a custom genetic algorithm. Simulation results show that the two proposed flow reconfiguration algorithms reduce the rule processing times and provide an efficient solution for increasing the scalability of the considered environment. Another aspect being discussed is using an open-source cloud solution to manage the system and how to use the two algorithms to increase efficiency. These methods allow for a seamless increase in the number of sensors in the environment by making smart use of the available resources.

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