Pattern generation from event oriented sensor data using distributed sensor transaction model
Amrit Pal, Manish Kumar · 2017
Amount of data generated by IoT devices is increasing day by day, it requires efficient and scalable infrastructure to store and process this data. Distributed process is an idle tool for analyzing this amount of data. Pattern mining of the IoT device events can result in better decision making in IoT eco-system. In this paper we have proposed a integrated environment for distributed data collection using a Mapreduce based technique exploiting distributed processing of the data. The proposed approach uses an Apriori and Mapreduce based algorithm for analyzing the data. Available dataset and synthetic datasets has been used for analysis and scalability test of the proposed approach. The approach shows a good amount of scalabity for mining the frequent patterns in event based sensor data.