no.usn:wiseflow:6592923:50570421.pdf
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Advances in 5G and Artificial Intelligence (AI) allow edge devices to shift to machine-to-machine communication (M2M), meaning edge nodes can process and analyse raw data of IoT devices. Introduction Cloud computing with an exponential growth of smart devices which can generate data, cloud centres f
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Summary
This document discusses the challenges faced by cloud computing due to the exponential growth of smart devices, such as bandwidth limitations, data privacy and security concerns, and response time and latency issues. It introduces edge computing as a solution to offload processing to local devices and resolve these challenges. The use of Artificial Intelligence (AI) and Blockchain is proposed for network security. The core concepts of edge computing are explained, with three layers: cloud, edge, and devices. Advances in 5G and AI enable machine-to-machine communication and data processing at the edge. Fog nodes and edge nodes play a role in data collection and processing.
Top Highlights
- Advances in 5G and Artificial Intelligence (AI) allow edge devices to shift to machine-to-machine communication (M2M), meaning edge nodes can process and analyse raw data of IoT devices.
- Introduction Cloud computing
- with an exponential growth of smart devices which can generate data, cloud centres face some problems with bandwidth, data privacy and security, response time and latency
- Edge computing is a new paradigm that has emerged to offload some processing to the local devices end resolve the above-mentioned issues with cloud technology and IoT
- from lack of education on when and how to use the technology (46%)
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