Edge computing
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Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, in order to improve response times and save bandwidth.
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Edge computing involves deploying small data centers or micro data centers (also called edge nodes) closer to the devices generating the data, such as sensors, smartphones, and IoT devices, in order to process the data in real-time or near-real-time.
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Edge computing can improve the performance, reliability, and security of applications, as well as reduce latency, bandwidth costs, and reliance on cloud services.
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Edge computing can be used in a variety of domains, such as healthcare, transportation, manufacturing, retail, and smart cities, where there is a need for real-time processing, low-latency communication, and high security.
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Edge computing architectures can be centralized, decentralized, or hybrid, depending on the distribution of computing resources and the coordination of data flow.
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Edge computing involves several technologies and standards, such as containerization, virtualization, [[ _notes/Teach Trends/Fog computing ]], [[ edge analytics ]], [[ edge caching ]], [[ edge security ]], and [[ edge orchestration ]].
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Edge computing faces several challenges and trade-offs, such as scalability, interoperability, heterogeneity, privacy, and data governance.
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Edge computing is expected to play a critical role in the development of emerging technologies, such as 5G, AI, AR/VR, autonomous vehicles, and the Internet of Things, by enabling faster and more intelligent processing of data at the edge of the network.
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Some of the key players in the edge computing market include cloud providers (such as Amazon Web Services, Microsoft Azure, and Google Cloud), hardware vendors (such as Cisco, Dell, and HPE), software vendors (such as VMware and Red Hat), and startups (such as MobiledgeX - Accedian and EdgeConneX (eqtgroup.com)).
Edge computing is expected to grow at a compound annual growth rate (CAGR) of 34.1% from 2020 to 2027, reaching $43.4 billion by 2027. Some of the factors driving this growth are:
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The increasing adoption of Internet of Things (IoT) devices and applications that generate large amounts of data at the edge of the network
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The rising demand for low-latency, real-time and high-performance computing for applications such as autonomous vehicles, smart cities, gaming and healthcare
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The emergence of 5G networks that enable faster and more reliable connectivity for edge devices
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The development of new technologies and standards that facilitate edge computing deployment and management, such as containers, microservices, serverless computing and multi-access edge computing (MEC)
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The growing awareness of the benefits of edge computing for security, privacy, scalability and cost-efficiency
[[ _notes/Teach Trends/Benefits of Edge Computing ]] [[ _notes/Teach Trends/Challenges or risks of Edge Computing ]] [[ _notes/Teach Trends/Use cases or examples of Edge Computing ]] [[ _notes/Teach Trends/How does edge computing relate to cloud computing? ]] [[ _notes/Teach Trends/Edge Computing with Web3 ]]