Edge Architecture Integration of Technologies

Edge Architecture Integration of Technologies

Sandhya Devi R. S. (Kumaraguru College of Technology, India), Vijaykumar V. R. (Anna University, Coimbatore, India), Sivakumar P. (PSG College of Technology, India), Neeraja Lakshmi A. (PSG College of Technology, India) and Vinoth Kumar B. (PSG College of Technology, India)
Copyright: © 2021 |Pages: 30
DOI: 10.4018/978-1-7998-4873-8.ch001
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Abstract

The enormous growth of the internet of things (IoT) and cloud-based services have paved the way for edge computing, the new computing paradigm which processes the data at the edge of the network. Edge computing resolves issues related to response time, latency, battery life limitation, cost savings for bandwidth, as well as data privacy and protection. The architecture brings devices and data back to the consumer. This model of computing as a distributed IT system aims at satisfying end-user demands with faster response times by storing data closer to it. The enormous increase in individuals and locations, connected devices such as appliances, laptops, smartphones, and transport networks that communicate with each other has raised exponentially. Considering these factors in this chapter, edge computing architecture along with the various components that constitute the computing platform are discussed. The chapter also discusses resource management strategies deliberate for edge computing devices and integration of various computing technologies to support efficient IoT architecture.
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Background

Shi et al. (2016) offer a detailed overview of edge computing, with the argument that computation will occur close data sources. It lists many instances where edge computing might flourish from offloading cloud to a smart ecosystem like home and area. It also implements interactive edge, as the edge can physically and theoretically connect end-user and cloud, and not only is the traditional cloud computing model still supported, but it can also bring long-distance networks together for data exchange and coordination due to device closeness. Lastly, it overviews the problems and opportunities worth focusing on, including programmability, naming, aggregation of data, service management, privacy, and protection, as well as metrics for optimization.

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