Energy Analysis and Application of Data Mining Algorithms for Internet of Things Based on Hadoop Cloud Platform
The paper analyses and studies the classication and characteristics of Internet of Things (IoT) information, and discusses the construction and application of Hadoop Cloud Platform. This paper mainly carries out from two aspects. One is to design the system architecture of the Open Platform for Data Simulation Resources of the IoT and design the key modules. A platform for data simulation resources of the IoT is built to provide the running environment and external services for the sensor data simulation model established. On the other hand, it is the key method to study the simulation data model based on IoT sensors. That is, based on the research environment of the IoT built by the existing laboratories, collect the data of sensors, analyze and study the characteristics of sensors in the IoT, and design the key algorithms for data simulation. This paper presents two key models for sensor data modeling: the Long Short-term Memory (LSTM) prediction model and the Support Vector Machine (SVM) model based on IoT data, which are suitable for different data volumes. Extensive simulations are executed to validate the remarkable nature in Hadoop platform, in terms of prediction accuracy and training efciency under different working condition.
Energy analysis, Internet of Things, cloud platform, Hadoop.