Measurement Method and Application of a Deep Learning Digital Economy Scale Based on a Big Data Cloud Platform

In recent years, with the acceleration of the process of economic globalization and the deepening of my country's financial liberalization, the scale of international short-term capital flows has been extremely rapid. This article mainly studies the deep learning digital economy scale measurement method and its application based on the big data cloud platform. This article uses the indirect method to estimate the stock of renminbi circulating abroad. The results show that the application of big data cloud platforms can increase the development share of digital media and digital transactions in the digital economy, and optimize the structure of China's digital economy.

A Review on AWS - Cloud Computing Technology

Cloud computing is something simple we can define as maintaining data centers and data servers and also u can access technology services by computing power, storage, and database using cloud computing technology AWS(Amazon Web Services). It is an emerged model which is already popular among almost all enterprises. It provides us the concept of ondemand services where we are using and scaling cloud resources on demand and as per demand respectively. AWS Cloud computing is a cost-effective model. The major concern in this model is Security and Storage in the cloud. This is one of the major reasons many enterprises of choosing AWS cloud computing. This paper provides a review of security research in the field of cloud security and storage services of the AWS cloud platform. After security and storage, we have presented the working of AWS (Amazon Web Service) cloud computing. AWS is the most trusted provider of cloud computing which not only provides excellent cloud security but also provides excellent cloud storage services. The main aim of this paper is to make cloud computing storage and security a core operation and not an add-on operation. As per the increase in the Service provider and related companies, this AWS Cloud Platform plays a vital role in service industries by giving its best web services, so, therefore, choosing the cloud service providers wisely is the basic need of the industry. Therefore we are going to see how AWS fulfills all these specific needs. Keywords: Trusted Computing, AWS, Information-Centric Security, Cloud Storage, S3, EC2, Cloud Computing

Big Data Precision Marketing Approach under IoT Cloud Platform Information Mining

In this article, an in-depth study and analysis of the precision marketing approach are carried out by building an IoT cloud platform and then using the technology of big data information mining. The cloud platform uses the MySQL database combined with the MongoDB database to store the cloud platform data to ensure the correct storage of data as well as to improve the access speed of data. The storage method of IoT temporal data is optimized, and the way of storing data in time slots is used to improve the efficiency of reading large amounts of data. For the scalability of the IoT data storage system, a MongoDB database clustering scheme is designed to ensure the scalability of data storage and disaster recovery capability. The relevant theories of big data marketing are reviewed and analyzed; secondly, based on the relevant theories, combined with the author’s work experience and relevant information, a comprehensive analysis and research on the current situation of big data marketing are conducted, focusing on its macro-, micro-, and industry environment. The service model combines the types of user needs, encapsulates the resources obtained by the alliance through data mining for service products, and publishes and delivers them in the form of data products. From the perspective of the development of the telecommunications industry, in terms of technology, the telecommunications industry has seen the development trend of mobile replacing fixed networks and triple play. The development of emerging technologies represented by the Internet of Things and cloud computing has also led to technological changes in the telecommunications industry. Operators are facing new development opportunities and challenges. It also divides the service mode into self-service and consulting service mode according to the different degrees of users’ cognition and understanding of the service, as well as proposes standardized data mining service guarantee from two aspects: after-sales service and operation supervision. A customized data mining service is a kind of data mining service for users’ personalized needs. And the intelligent data mining service guarantee is proposed from two aspects of multicase experience integration and group intelligence. In the empirical research part, the big data alliance in Big Data Industry Alliance, which provides data mining service as the main business, is selected as the research object, and the data mining service model of the big data alliance proposed in this article is applied to the actual alliance to verify the scientific and rationality of the data mining service model and improve the data mining service model management system.

Design of Monitoring and Controlling System for Smart Home

An intelligent lifestyle has become a hotspot for researchers and industries nowadays. The smart home monitoring and controlling system with the Arduino as the main controller is designed in this paper, combined with sensors, Wi-Fi, and cloud technologies. Various sensors collect household environmental information, such as indoor temperature and humidity, soil moisture, combustible gas concentration, and light intensity. The main controller processes the collected signals and automatically operates the devices, including a refrigeration equipment, water pump, buzzer, fan, stepping motor. The data can also be transmitted to the cloud platform through Wi-Fi for processing, and the home environment information and device can be remotely monitored and controlled by the cloud platform or smartphone APP.

Research on New Virtualization Security Protection Management System Based on Cloud Platform

As an emerging product under the condition of informatization, the utilization of cloud platform in many industries has brought fundamental changes to the production and business model in related fields. The cloud platform provides rich and diverse utilization services to terminals through multi-dimensional integration of different IT resources. With the in-depth utilization of cloud platform, the security problems it faces are becoming more and more prominent. The traditional network security protection means have been difficult to effectively adapt to and deal with the security threats under the new situation of cloud platform utilization. As a prominent part of building cloud platform, the construction level of virtualization security protection system will have an intuitive impact on the security of cloud platform. At present, the virtualization security protection management system under cloud platform is facing direct threats from virtual machine deployment, virtual machine communication and virtual machine migration. Based on this, this paper studies the virtualization security protection management system of cloud platform from the perspective of virtualization security tech, so as to ameliorate the stability, reliability and security of cloud platform.

Hybrid Autoscaling Strategy on Container-based Cloud Platform

The container has several advantages over the traditional virtual machine technology such as light-weight, fast booting time, and fast recovery. Kubernetes is one the most outstanding container management and deployment platforms. The Kubernetes provides autoscaling function, which will increase and decrease the hardware resources to adapt with the current traffic load situation to keep the user experience. Two popular autoscaling methods are horizontal autoscaling and vertical autoscaling. Based on the monitoring resource utilization, horizontal autoscaling will increase the number of PoDs (point of deployment) or vertical autoscaling will increase the hardware resources of each PoD to achieve the target utilization. In this paper, we present a hybrid solution that combines the advantages of both autoscaling solutions and proposes a bandwidth-efficient scheduler strategy. By numerical analysis, our hybrid approach is better than the normal HPA approach in terms of bandwidth cost and has lower autoscaling latency than the VPA approach