Comparative Analysis of Virtualization Methods in Big Data Processing

Радченко, Глеб; Alaasam, Ameer B. A.; Tchernykh, Andrei

doi:10.14529/jsfi190107

Cited by 12 publications

(6 citation statements)

References 60 publications

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“…Virtualization allows for the abstraction of the hardware present on a physical machine [18]. This abstraction allows for greater control over access to the devices present on the hardware level of the machine.…”

Section: Containerizationmentioning

confidence: 99%

Containerization in Edge Intelligence: A Review

Urblik,

Kajati,

Papcun

et al. 2024

Electronics

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The onset of cloud computing brought with it an adoption of containerization—a lightweight form of virtualization, which provides an easy way of developing and deploying solutions across multiple environments and platforms. This paper describes the current use of containers and complementary technologies in software development and the benefits it brings. Certain applications run into obstacles when deployed on the cloud due to the latency it introduces or the amount of data that needs to be processed. These issues are addressed by edge intelligence. This paper describes edge intelligence, the deployment of artificial intelligence close to the data source, the opportunities it brings, along with some examples of practical applications. We also discuss some of the challenges in the development and deployment of edge intelligence solutions and the possible benefits of applying containerization in edge intelligence.

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Section: Containerizationmentioning

confidence: 99%

Containerization in Edge Intelligence: A Review

Urblik,

Kajati,

Papcun

et al. 2024

Electronics

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“…Authors of [72] present a comparative analysis of both types of virtualization, based on which we can highlight some of the advantages of container-based virtualization.…”

Section: Virtualizationmentioning

confidence: 99%

Fog computing state of the art: concept and classification of platforms to support distributed computing systems

Kirsanova¹,

Радченко²,

Tchernykh³

2021

Preprint

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As the Internet of Things (IoT) becomes a part of our daily life, there is a rapid growth in the connected devices. A well-established approach based on cloud computing technologies cannot provide the necessary quality of service in such an environment, particularly in terms of reducing data latency. Today, fog computing technology is seen as a novel approach for processing large amounts of critical and time-sensitive data. This article reviews cloud computing technology and analyzes the prerequisites for the evolution of this approach and the emergence of the concept of fog computing. As part of an overview of the critical features of fog computing, we analyze the frequent confusion of the concepts of fog and edge computing. We provide an overview of fog computing technologies: virtualization, containerization, orchestration, scalability, parallel computing environments, as well as a systematic analysis of the most popular platforms that support fog computing. As a result of the analysis, we offer two approaches to classification of the fog computing platforms: by the principle of openness/closure of components and a three-level classification based on the provided platform functionality (Deploy-, Platform-and Ecosystem as a Service).

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“…Today, cloud computing systems have become widely used for Big Data processing, providing access to a wide variety of computing resources and a greater distribution between multiclouds [73]. This trend has been strengthened by the rapid development of the Internet of Things (IoT) concept.…”

Section: Key Features Of Cloud Computingmentioning

confidence: 99%

“…Authors of [73] present a comparative analysis of both types of virtualization, based on which we can highlight some of the advantages of container-based virtualization.…”

Section: Virtualizationmentioning

confidence: 99%

Fog Computing State of the Art: Concept and Classification of Platforms to Support Distributed Computing Systems

Kirsanova

Радченко

Tchernykh

2021

JSFI

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As the Internet of Things (IoT) becomes a part of our daily life, there is a rapid growth in the connected devices. A well-established approach based on cloud computing technologies cannot provide the necessary quality of service in such an environment, particularly in terms of reducing data latency. Today, fog computing technology is seen as a novel approach for processing large amounts of critical and time-sensitive data. This article reviews cloud computing technology and analyzes the prerequisites for the evolution of this approach and the emergence of the concept of fog computing. As part of an overview of the critical features of fog computing, we analyze the frequent confusion of the concepts of fog and edge computing. We provide an overview of fog computing technologies: virtualization, containerization, orchestration, scalability, parallel computing environments, as well as systematic analysis of the most popular platforms that support fog computing. As a result of the analysis, we offer two approaches to classification of the fog computing platforms: by the principle of openness/closure of components and by the three-level classification based on the provided platform functionality (Deploy-, Platform-and Ecosystem as a Service).

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Comparative Analysis of Virtualization Methods in Big Data Processing

Cited by 12 publications

References 60 publications

Containerization in Edge Intelligence: A Review

Containerization in Edge Intelligence: A Review

Fog computing state of the art: concept and classification of platforms to support distributed computing systems

Fog Computing State of the Art: Concept and Classification of Platforms to Support Distributed Computing Systems

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