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Predictive Analytics in Cloud, Fog, and Edge Computing
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Predictive Analytics in Cloud, Fog, and Edge ComputingНазвание: Predictive Analytics in Cloud, Fog, and Edge Computing: Perspectives and Practices of Blockchain, IoT, and 5G
Автор: Hiren Kumar Thakkar, Chinmaya Kumar Dehury, Prasan Kumar Sahoo, Bharadwaj Veeravalli
Издательство: Springer
Год: 2023
Страниц: 252
Язык: английский
Формат: pdf (true), epub
Размер: 33.5 MB

This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G.

In the recent past, the number of connected devices has grown exponentially, leading to enormous amount of raw data generation. However, abundant amount of raw data is meaningless unless analysed to mine the informative patterns. In this regard, raw data need to be process and analysed at device level (edge computing), network level (fog computing), and in the data centre (Cloud computing). Designing an efficient predictive algorithm is a challenging task at device level as well as network level considering the limitations of computation power. On the contrary, cloud computing supports massive computation capacity to design an efficient predictive algorithm, but it suffers due to the high latency. Additionally, attempts are made to integrate the cross technologies such as blockchain, IoT, and 5G with cloud computing for better application designing and support. This book attempts to provide a comprehensive review of edge, fog, and cloud computing with detailed description on their applicability, limitations, and how each technology complements each other. Moreover, the book focuses on predictive analytics in cloud, fog, and edge computing as well as on perspectives and practices of blockchain, IoT, and 5G. It covers the domains such as healthcare security in cloud computing, watermarked medical image transmission over the cloud, role of blockchain in cloud computing, cloud-based smart controlled environment designing, serverless data pipelines for IoT data analytics, impact of 5G technologies on cloud analytics, and 5G-enabled smart city using cloud environment.

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