The Rise of Big Data, Cloud, and Internet of Things

Author(s):  
Reema Abdulraziq ◽  
Muneer Bani Yassein ◽  
Shadi Aljawarneh

Big data refers to the huge amount of data that is being used in commercial, industrial and economic environments. There are three types of big data; structured, unstructured and semi-structured data. When it comes to discussions on big data, three major aspects that can be considered as its main dimensions are the volume, velocity, and variety of the data. This data is collected, analysed and checked for use by the end users. Cloud computing and the Internet of Things (IoT) are used to enable this huge amount of collected data to be stored and connected to the Internet. The time and the cost are reduced by means of these technologies, and in addition, they are able to accommodate this large amount of data regardless of its size. This chapter focuses on how big data, with the emergence of cloud computing and the Internet of Things (IOT), can be used via several applications and technologies.

2019 ◽  
Vol 9 (23) ◽  
pp. 5159 ◽  
Author(s):  
Shichang Xuan ◽  
Yibo Zhang ◽  
Hao Tang ◽  
Ilyong Chung ◽  
Wei Wang ◽  
...  

With the arrival of the Internet of Things (IoT) era and the rise of Big Data, cloud computing, and similar technologies, data resources are becoming increasingly valuable. Organizations and users can perform all kinds of processing and analysis on the basis of massive IoT data, thus adding to their value. However, this is based on data-sharing transactions, and most existing work focuses on one aspect of data transactions, such as convenience, privacy protection, and auditing. In this paper, a data-sharing-transaction application based on blockchain technology is proposed, which comprehensively considers various types of performance, provides an efficient consistency mechanism, improves transaction verification, realizes high-performance concurrency, and has tamperproof functions. Experiments were designed to analyze the functions and storage of the proposed system.


Author(s):  
Vardan Mkrttchian ◽  
Leyla Gamidullaeva ◽  
Svetlana Panasenko ◽  
Arman Sargsyan

This chapter discusses the problems associated with the design of the business model in the new context of big data and the internet of things to create a research laboratory for studying and improving digital transformations. The development of business prospects for IOT is due to two main trends: 1) the change of focus from IOT viewing primarily as a technology platform for viewing it as a business ecosystem and 2) the transition from focusing on the business model in general to the development of business models of ecosystems. In the chapter, the business model of the ecosystem is considered as a model consisting of signs fixed in ecosystems and focuses on creating the cost of the laboratory and fixing the value of the ecosystem in which the created laboratory operates.


2022 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Gustavo Grander ◽  
Luciano Ferreira da Silva ◽  
Ernesto D. R. Santibanez Gonzalez

Studies concerning Big Data patents have been published; however, research investigating Big Data projects is scarce. Therefore, the objective of this study was to conduct an exploratory analysis of a patent database to collect information about the characteristics of registered patents related to Big Data projects. We searched for patents related to Big Data projects in the Espacenet database on January 10, 2021, and identified 109 records.. The textual analysis detected three word classes interpreted as (i) a direction to cloud computing, (ii) optimization of solutions, and (iii) storage and data sharing structures. Our results also revealed emerging technologies such as Blockchain and the Internet of Things, which are utilized in Big Data project solutions. This observation demonstrates the importance that has been given to solutions that facilitate decision-making in an increasingly data-driven context. As a contribution, we understand that this study endorses a group of researchers that has been dedicated to academic research on patent documents.


The initiation of the Internet of Things is the fundamental stimulus behind the current mechanical surprise. Web of things is the unavoidable aggregation of web related devices that assemble, look at and change the immense measure of colossal data at an incomparable rate. By creating and passing on sensible preprocessing frameworks, this goliath measurement of data can be transformed into performance information. The all-new IoT tremendous information development expects changes to be passed on to the present advances. The significance of preprocessing methodologies in the IoT enormous information situation has been discussed in this document and in addition to early IoT examines huge information preprocessing frameworks. Finally, a bright fresh parallel preprocessing system for IoT Big data has been suggested to transform the tough data into treasurable information so that enormous data examination of IoT performance can obtain complete recognition of this increasing growth


Author(s):  
Pasumpon Pandian A

The edge computing that is an efficient alternative of the cloud computing, for handling of the tasks that are time sensitive, has become has become very popular among a vast range of IOT based application especially in the industrial sides. The huge amount of information flow and the services requisition from the IOT has made the traditional cloud computing incompatible on the time of big data flow. So the paper proposes an enhanced edge model for the by incorporating the artificial intelligence along with the integration of caching to the edge for handling of the big data flow in the applications of the internet of things. The performance evaluation of the same in the network simulator 2 for enormous flow of task that are time sensitive , evinces that the proposed method has a minimized delay compared the traditional cloud computing models.


Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.


Author(s):  
Anchitaalagammai J. V. ◽  
Kavitha S. ◽  
Murali S. ◽  
Padmadevi S. ◽  
Shanthalakshmi Revathy J.

The internet of things (IoT) is rapidly changing our society to a world where every “thing” is connected to the internet, making computing pervasive like never before. It is increasingly becoming a ubiquitous computing service, requiring huge volumes of data storage and processing. Unfortunately, due to the lack of resource constraints, it tends to adopt a cloud-based architecture to store the voluminous data generated from IoT application. From a security perspective, the technological revolution introduced by IoT and cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. This chapter focus on security considerations for IoT from the perspectives of cloud tenants, end-users, and cloud providers in the context of wide-scale IoT proliferation, working across the range of IoT technologies. Also, this chapter includes how the organization can store the IoT data on the cloud securely by applying different Access control policies and the cryptography techniques.


Author(s):  
Anna Smyshlyaeva ◽  
Kseniya Reznikova ◽  
Denis Savchenko

With the advent of the Industry 4.0 concept, the approach to production automation has fundamentally changed. The manufacturing industry is based on such modern technologies as the Internet of Things, Big Data, cloud computing, artificial intelligence and cyber-physical systems. These technologies have proven themselves not only in industry, but also in various other branches of life. In this paper, the authors consider the concept of cyber-physical systems – systems based on the interaction of physical processes with computational ones. The article presents a conceptual model of cyber-physical systems that displays its elements and their interaction. In cyber-physical systems, it represents five levels: physical, network, data storage, processing and analytics level, application level. Cyber-physical systems carry out their work using a basic set of technologies: the Internet of things, big data and cloud computing. Additional technologies are used depending on the purpose of the system. At the physical level, data is collected from physical devices. With the help of the Internet of Things at the network level, data is transferred to a data warehouse for further processing or processed almost immediately thanks to cloud computing. The amount of data in cyber-physical systems is enormous, so it is necessary to use big data technology and effective methods for processing and analyzing this data. The main feature of this technological complex is real-time operation. Despite the improvement in the quality of production and human life, cyber-physical systems have a number of disadvantages. The authors highlight the main problems of cyber-physical systems and promising areas of research for their development. Having solved the listed problems, cyber-physical systems will reach a qualitatively new level of utility. The paper also provides examples of the implementation of concepts such as a smart city, smart grid, smart manufacturing, smart house. These concepts are based on the principle of cyber-physical systems.


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