Design And Implentation Of Distributed Universal IoT Data Management Platform

With the rapid development of the IoT technology,more and more sensing devices will be connected to the IoT platform.These IoT sensing devices will generate large amounts of data,and the management of these data is a very important task.The traditional IoT platforms have the disadvantages of fixed data processing mode and low processing efficiency.In order to solve this problem,a universal platform needs to be designed so that users can complete the data management according to their own needs.This thesis aims to design an universal IoT data management platform,which can be connected to a variety of different devices and used in different industries to achieve the goal of IoT data management,including data access,data processing,data storage,data distribution and other aspects.A rule engine is designed on this platform to realize data processing,storage and distribution functions,so that users can customize the data processing methods according to their own needs to meet users'individual needs for data processing.In this thesis,through investigation of existing IoT platforms and requirement analysis,in order to ensure the reliability and stability of the system,this platform is designed as a distributed system,deployed as a cluster,and the cluster is coordinated and managed by ZooKeeper.Based on the requirements analysis,the business module of the server side is divided into five modules:user management,device management,data access,rule engine and file processing.The data access module uses the MQTT protocal based on the publish and subscribe mode,and use the NIO-based Netty framework to complete the MQTT client.The file processing modules uses the HDFS.The rule engine design allows users to customize the rules of data flow and data processing.In the end of this thesis,a comprehensive test of the IoT platform is carried out.The results of the test verify the feasibility and effectiveness of the platform.