Energy Analysis and Application of Data Mining Algorithms for Internet of Things Based on Hadoop Cloud Platform

Abstract

The paper analyses and studies the classification 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 efficiency under different working condition. INDEX TERMS Energy analysis, Internet of Things, cloud platform, Hadoop.

Replication-Based Query Management for Resource Allocation Using Hadoop and MapReduce over Big Data

“…The activity and node failure is taken into account, and delays are reduced. Two types of documents, i.e., checkpoint files and index files, are introduced, which are international documents created prior to implementing a single-sized task [26] . The sanctuary is in charge of preventing the execution of the current work of checkpoint documents.…”

Management Challenges and Opportunities for Energy Cloud Development and Diffusion

“…Another important task to be highlighted is that there must be a selection of the data that will be sent to the cloud, which relieves the data transmission networks [46,57]. However, perhaps one of the challenges that most impacts the companies that manufacture the components of this layer is the need for convergence toward standardization, which makes it possible to integrate different technologies and devices [16,17,59,99] by bringing facilities to users, companies, and service providers as well as contributing to the dissemination and use of the concept of ECM.…”

“…These technologies are used to transfer the data from the fog to the cloud layer for further processing [27,46], and this data transmission occurs over a long distance, from users' domains to where the cloud data centers are located. Thus, since the network saturation level is a constant concern [57,82,98,99], it is important to choose a communication medium with appropriate bandwidth for a large amount of data transportation between fog and cloud layers [98]. Considering this concern and the mobile network technologies available, such as Second Generation (2G), Third Generation (3G), Fourth Generation (4G), Fifth Generation (5G), General Packet Radio Service/Code Division Multiple Access (GPRS/CDMA), and Global System for Mobile Communication (GSM), improvements in connectivity levels and mobility of data and communications networks are important challenges related to networks to be overcome [50,53,82].…”

Big data analysis and application of library information resources

“…At the same time, Python's Jison library, combined with the above two third-party libraries, can be used to realize the application of web crawlers in the construction of literature information resources through the automatic submission of search keywords [9][10]. Actively exploring the application of big data web crawler technology in the field of intelligent library information resources, we have realized the web crawler of China's latest book rankings as well as the web crawler on literature information resources, which provides strong support for the construction of information resources in intelligent libraries [11][12][13].…”