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Edge Computing on IoT: Architectures, Techniques, and Challenges

Edge Computing on IoT: Architectures, Techniques, and Challenges
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Author(s): Mahalakshmi R. (Presidency University, India), Uzra Ismat (Presidency University, India) and Praveena K. N. (Presidency University, India)
Copyright: 2023
Pages: 31
Source title: New Approaches to Data Analytics and Internet of Things Through Digital Twin
Source Author(s)/Editor(s): P. Karthikeyan (National Chung Cheng University, Chiayi, Taiwan), Polinpapilinho F. Katina (University of South Carolina Upstate, USA) and S.P. Anandaraj (Presidency University, India)
DOI: 10.4018/978-1-6684-5722-1.ch004

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Abstract

The internet of things (IoT) is escalating into diverse aspects of our lives with innovative technologies and solutions. In general, IoT devices are restricted to storage and processing power, which results in the lack of performance, reliability, and privacy of IoT applications. The applications in various sectors like agriculture, healthcare, smart cities, smart homes, and production units are enriched by twining the IoT and cloud computing. Cloud analytics is the process of extracting actionable business insights from the data stored in the cloud. Cloud analytics algorithms are applied to large data collections to identify patterns, predict future outcomes, and produce other useful information to business decision makers. Edge computing has arisen to support this intense increase in resource requirements by leveraging the untouched potential away from the enterprise data cores. Processing power is gained by a collective process between various entities at the network edge including the user devices, mobile-based stations, and gateways and access points.

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