Virtual technology of cache and real-time big data distribution in cloud computing big data center

2020 ◽  
Vol 39 (6) ◽  
pp. 8917-8925
Author(s):  
Bing Zheng ◽  
Xiaoying Zhang ◽  
Dawei Yun
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Real Time ◽  
Data Center ◽  
System Change ◽  
Virtual Technology ◽  
Topology Model ◽  
Network Platform ◽  
Efficient Transmission ◽  
Traditional Understanding

By comparing several cloud computing of big data network center during COVID-19, this paper proposes a new topology model, which realizes two functions of cloud computing big data center caching and big data real-time distribution. In addition, cloud computing network requires higher performance than traditional application big data center, which makes the consideration of network platform construction performance different from the traditional understanding. During COVID-19, we deeply understood the underlying attributes of cloud, combined with the topology model, we can realize the decoupling of cloud computing big data system, change the situation of direct connection between upstream and downstream, and have more reliable and efficient transmission of message and command big data.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

scholarly journals Application of Big Data Fusion Based on Cloud Storage in Green Transportation: An Application of Healthcare

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Qin Hu ◽  
Amit Yadav ◽  
Asif Khan ◽  
Hong Liu ◽  
Amin Ul Haq
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Fusion ◽  
Real Time ◽  
Strong Support ◽  
Heterogeneous Data ◽  
Continuous Growth ◽  
New Energy ◽  
The Government ◽  
Vehicle Network

In the 21st century, transportation brought great convenience to people, but at the same time, automobile transportation is the major factor causing greenhouse gas emissions and climate change. Movements of the world towards green environments, there is hike in use and production of electric vehicles (energy vehicles). However, with the continuous growth in the number of energy vehicles, it is necessary for the government to provide strong support in the construction of charging piles. Real-time and effective management has become a practical problem for the relevant departments which needs to be solved. This paper uses the information research method to fuse the huge amount of heterogeneous data generated by the charging pile resultant to the new energy electric vehicle in the vehicle network and introduces cloud computing as its storage module to facilitate the storage and related expansion of the big data. This paper proposes a system scheme of heterogeneous data fusion based on cloud computing for the acquisition, storage, and fusion of heterogeneous data in the vehicle network. After testing the results, it shows that the system is stable and effective in practical application, which can meet the design requirements of the system. What is the significance of analyzing big data of charging point? Considering from the supply side, obtaining the user’s charging behaviour data is helpful to build a digital map of the charging pile of new energy vehicles, connect the service information between the vehicle enterprises and the charging pile enterprises, and provide the most comprehensive and effective real-time charging information covering the widest range of vehicles, which can solve many problems of information asymmetry in the current charging information service.

scholarly journals Designing Efficient Smart Home Management with IoT Smart Lighting: A Case Study

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Tran Anh Khoa ◽  
Le Mai Bao Nhu ◽  
Hoang Hai Son ◽  
Nguyen Minh Trong ◽  
Cao Hoang Phuc ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Information Security ◽  
Internet Of Things ◽  
Real Time ◽  
Mobile Networks ◽  
Smart Home ◽  
Smart Cities ◽  
Smart Homes ◽  
Authentication Mechanism

Smart homes are an element of developing smart cities. In recent years, countries around the world have spared no effort in promoting smart cities. Smart homes are an interesting technological advancement that can make people’s lives much more convenient. The development of smart homes involves multiple technological aspects, which include big data, mobile networks, cloud computing, Internet of Things, and even artificial intelligence. Digital information is the main component of signal control and flow in a smart home, while information security is another important aspect. In the event of equipment failure, the task of safeguarding the system’s information is of the utmost importance. Since smart homes are automatically controlled, the problem of mobile network security must be taken seriously. To address these issues, this paper focuses on information security, big data, mobile networks, cloud computing, and the Internet of Things. Security efficiency can be enhanced by using a Secure Hash Algorithm 256 (SHA-256), which is an authentication mechanism that, with the help of the user, can authenticate each interaction of a given device with a WebServer by using an encrypted username, password, and token. This framework could be used for an automated burglar alarm system, guest attendance monitoring, and light switches, all of which are easily integrated with any smart city base. In this way, IoT solutions can allow real-time monitoring and connection with central systems for automated burglar alarms. The monitoring framework is developed on the strength of the web application to obtain real-time display, storage, and warning functions for local or remote monitoring control. The monitoring system is stable and reliable when applying SHA-256.

Replication Policy of Real-Time Distributed System for Cloud Computing

2015 ◽  
Vol 22 (05) ◽  
pp. 1550024
Author(s):  
Mitsutaka Kimura ◽  
Mitsuhiro Imaizumi ◽  
Toshio Nakagawa
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Center ◽  
Cloud System ◽  
Next Generation ◽  
Distributed Information ◽  
Intelligent Node ◽  
Client Data ◽  
Information And Communication ◽  
Processing Architecture

Recently, cloud computing has been widely used for the purpose of protecting client data on the Internet [A. Weiss, Computing in the clouds, netWorker11 (2007) 16–25; M. Armbrust et al., Above the clouds: A Berkeley view of cloud computing, Technical Report UCV/EECS-2009-28, University of California at Berkeley (2009)]. But when a client receives network service, response time may be slow because the data center is located in a remote place. In order to solve the problem, real-time distributed systems for cloud computing has been proposed [M. Okuno, D. Ito, H. Miyamoto, H. Aoki, Y. Tsushima and T. Yazaki, A study on distributed information and communication processing architecture for next generation cloud system, IEICE Tech. Report109(A48) (2010) 241–246; M. Okuno, S. Tsutsumi and T. Yazaki, A study of high available distributed network processing technique for next generation cloud system, IEICE Tech. Report111(8) (2011) 25–30; S. Yamada, J. Marukawa, D. Ishii, S. Okamoto and N. Yamanaka, A study of parallel transmission technique with GMPLS in intelligent cloud network, IEICE Tech. Report109(455) (2010) 51–56]. The cloud computing system consists of some intelligent nodes as well as a data center. The data center manages all client data. The intelligent node provides client service near clients. It enables to provide client service at short response time [M. Okuno, D. Ito, H. Miyamoto, H. Aoki, Y. Tsushima and T. Yazaki, A study on distributed information and communication processing architecture for next generation cloud system, IEICE Tech. Report109(448) (2010) 241–246]. We considered the reliability model of distributed information processing for cloud computing, derived cost effectiveness and discussed the optimal replication interval to minimize it [M. Kimura, M. Imaizumi and T. Nakagawa, Reliability modeling of distributed information processing for cloud computing, in Proc. 20th ISSAT Int. Conf. Reliability and Quality in Design (2014), pp. 183–187]. Authors had dealt with the server system with one failure mode. In this paper, we consider the reliability model of a real-time distributed system with n intelligent nodes and formulate a stochastic model of the server system with n intelligent nodes for changing the other normal intelligent node at failure. We derive the expected numbers of the replication and of updating the client data. Further, we derive the expected cost and discuss an optimal replication interval to minimize it. Next, we derive the cost effectiveness and discuss an optimal number of intelligent nodes to minimize it.

scholarly journals The application of e-commerce recommendation system in smart cities based on big data and cloud computing

2021 ◽  
pp. 26-26
Author(s):  
Yiman Zhang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Collaborative Filtering ◽  
Real Time ◽  
Evaluation System ◽  
Recommendation System ◽  
Smart Cities ◽  
Personalized Recommendation ◽  
Current Recommendation ◽  
Recommendation Algorithm

In the era of big data, the amount of Internet data is growing explosively. How to quickly obtain valuable information from massive data has become a challenging task. To effectively solve the problems faced by recommendation technology, such as data sparsity, scalability, and real-time recommendation, a personalized recommendation algorithm for e-commerce based on Hadoop is designed aiming at the problems in collaborative filtering recommendation algorithm. Hadoop cloud computing platform has powerful computing and storage capabilities, which are used to improve the collaborative filtering recommendation algorithm based on project, and establish a comprehensive evaluation system. The effectiveness of the proposed personalized recommendation algorithm is further verified through the analysis and comparison with some traditional collaborative filtering algorithms. The experimental results show that the e-commerce system based on cloud computing technology effectively improves the support of various recommendation algorithms in the system environment; the algorithm has good scalability and recommendation efficiency in the distributed cluster, and the recommendation accuracy is also improved, which can improve the sparsity, scalability and real-time problems in e-commerce personalized recommendation. This study greatly improves the recommendation performance of e-commerce, effectively solves the shortcomings of the current recommendation algorithm, and further promotes the personalized development of e-commerce.

scholarly journals Seminar dan Workshop Internet of Things guna merealisasikan Pembelajaran Industri 4.0 di Sekolah dan Masyarakat

2021 ◽  
Vol 1 (1) ◽  
pp. 24-30
Author(s):  
Lukman Rosyidi ◽  
Muh Syaiful Romadhon
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Real Time

Revolusi Industri 4.0 telah membawa perubahan pada dunia. Berbagai teknologi baru seperti cloud computing, Internet of things, Big Data, artificial intelligence, dan advance robotics telah dan akan mengubah cara manusia dalam bekerja dan menjalankan kehidupan. Internet of things, atau dikenal juga dengan IoT, merupakan sebuah teknologi yang bertujuan untuk memperluas manfaat dari konektivitas internet yang tersambung secara terus-menerus. Saat ini, Internet of things(IoT) telah secara luas digunakan untuk meningkatkan kualitas kehidupan manusia. Kasus aplikasi IoT yang paling umum adalah mengumpulkan informasi tentang suatu obyek secara real time untuk kegiatan pemantauan dan analisis data. Informasi ini akan berguna untuk memberikan layanan yang lebih baik atau meningkatkan produktivita. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk menyebarluaskan pengetahuan pemrograman IoT untuk pemula, sebagai dasar untuk penguasaan penerapan IoT dan pembelajaran IoT pada tingkatan berikutnya. Antusiasme dan respon yang diberikan para peserta juga sangat bagus. Rata-rata peserta memberikan jawaban sangat puas dengan presentase sebesr 71%. Hanya 3% yang menjawab cukup puas sedangkan sisanya menjawab puas. Seluruh peserta sama sekali tidak ada yang menjawab puas dan kurang puas.

scholarly journals Application of Big Data Analysis and Cloud Computing in Network Platform Building

2021 ◽  
Vol 2033 (1) ◽  
pp. 012114
Author(s):  
Jichao Sun ◽  
Tao Liu ◽  
Yong Wang ◽  
Ping Zhang ◽  
Dan Yang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Network Platform
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