scholarly journals Exploration of new generation city bus informationization system based on Internet of Things and cloud computing technology

Author(s):  
Hua Zhao
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Fuan Zhang ◽  
Zhenzhi Gong

With the development of economic globalization, the competition among enterprises is increasingly fierce. Therefore, companies need close information sharing to realize the integration of supply chain. This article aims to study the collaborative management and information sharing mechanism of supply chain inventory based on cloud computing and 5G Internet of Things. This article first introduces the theory and methods of collaborative supply chain management and the information exchange mechanism and then discusses the problem of information sharing in the supply chain, that is, the bullwhip phenomenon, and then from the demand forecast, supply chain structure, time lag, and shortage game, six aspects are analyzed. The cause of the bullwhip phenomenon is analyzed. Secondly, this article proposes a quantitative analysis of the bullwhip effect, establishes a mathematical model of the bullwhip effect in the supply chain, and uses quantitative analysis to analyze the value of information sharing in the supply chain. Finally, this article uses cloud computing technology to build a supply chain information collaboration system architecture and uses EPC Internet of Things to build a supply chain information sharing model and describes the entire operation process of the supply chain. The experimental results of this paper show that the application of cloud computing technology to supply chain management establishes a system platform for supply chain information sharing, improves the overall operational efficiency of supply chain management, and realizes supply chain information sharing and business collaboration. In addition, the operating costs and risks of each node enterprise in the supply chain are reduced by 12% compared with the nonsharing situation, which also shows that the overall benefits of the supply chain have been correspondingly improved and market competitiveness has been enhanced.


2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Zhenzhong Zhang ◽  
Wei Sun ◽  
Yanliang Yu

With the vigorous development of the Internet of Things, the Internet, cloud computing, and mobile terminals, edge computing has emerged as a new type of Internet of Things technology, which is one of the important components of the Industrial Internet of Things. In the face of large-scale data processing and calculations, traditional cloud computing is facing tremendous pressure, and the demand for new low-latency computing technologies is imminent. As a supplementary expansion of cloud computing technology, mobile edge computing will sink the computing power from the previous cloud to a network edge node. Through the mutual cooperation between computing nodes, the number of nodes that can be calculated is more, the types are more comprehensive, and the computing range is even greater. Broadly, it makes up for the shortcomings of cloud computing technology. Although edge computing technology has many advantages and has certain research and application results, how to allocate a large number of computing tasks and computing resources to computing nodes and how to schedule computing tasks at edge nodes are still challenges for edge computing. In view of the problems encountered by edge computing technology in resource allocation and task scheduling, this paper designs a dynamic task scheduling strategy for edge computing with delay-aware characteristics, which realizes the reasonable utilization of computing resources and is required for edge computing systems. This paper proposes a resource allocation scheme combined with the simulated annealing algorithm, which minimizes the overall performance loss of the system while keeping the system low delay. Finally, it is verified through experiments that the task scheduling and resource allocation methods proposed in this paper can significantly reduce the response delay of the application.


2020 ◽  
pp. 100175 ◽  
Author(s):  
Swati Dhingra ◽  
Rajasekhara Babu Madda ◽  
Rizwan Patan ◽  
Pengcheng Jiao ◽  
Kaveh Barri ◽  
...  

2015 ◽  
Vol 791 ◽  
pp. 42-48 ◽  
Author(s):  
Monika Kulisz ◽  
Jakub Pizoń

Internet of Things (IoT) is a technology enabling identification of individual devices, providing mutual communication between them and their user, and allowing them to cooperate. What is more, IoT delivers tools for simplification of monitoring and controlling of processes. The present article introduces an evolved solution to the Internet of Things usage in a machine cutting process of laminated boards relying on the Cloud Computing technology.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chien-Fu Cheng ◽  
Jerry Chun-Wei Lin ◽  
Gautam Srivastava ◽  
Chu-Chiao Hsu

The combination of the Internet of Things (IoT) and Cloud computing are both popular applications that are based on the Internet. However, the traditional networking structure can no longer support the transmission of the huge number of packets required by cloud computing and IoT. Therefore, a new-generation architecture, software-defined networking (SDN), came into being. The new-generation SDN can control routing through software, making flexible and convenient management a key feature of SDN. However, attacks and threats are prevalent in today’s networking environment. When an SDN controller encounters a hacker attack or virus infection, it will not function properly. Hence, we need to design a fault-tolerant mechanism for the above environment. In this paper, a fault-tolerant consensus protocol is proposed to improve the fault tolerance of SDNs with multiple controllers.


Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra

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.


2021 ◽  
Vol 27 (spe2) ◽  
pp. 27-30
Author(s):  
Weidong Yang ◽  
Huan Huang

ABSTRACT For athletes under training, it is more efficient to use the Internet of Things (IoT) and cloud computing methods to collect and process biochemical indicators, and this study is about research based on the IoT and cloud computing technology for athletes under training. The problems are put forward in this study. The requirements of related algorithm design and the communication model properties are comprehensively analyzed. Scheduling the link and allocating the transmit power of the nodes are comprehensively considered, with design and analysis of wireless sensor network scheduling algorithm. The factors influencing the scheduling efficiency of the algorithm are analyzed, considering the node density and the influence of different power allocation schemes on the scheduling result. This study shows that the algorithm of this thesis can collect the biochemical index data of athletes during training period. As the number of nodes increases, the running results will gradually move towards the optimal value. This research study is of important theoretical significance for the application of IoT and cloud computing technology and the improvement of athlete training effect.


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