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- W4200152024 endingPage "196" @default.
- W4200152024 startingPage "196" @default.
- W4200152024 abstract "Cloud computing has become integral lately due to the ever-expanding Internet-of-things (IoT) network. It still is and continues to be the best practice for implementing complex computational applications, emphasizing the massive processing of data. However, the cloud falls short due to the critical constraints of novel IoT applications generating vast data, which entails a swift response time with improved privacy. The newest drift is moving computational and storage resources to the edge of the network, involving a decentralized distributed architecture. The data processing and analytics perform at proximity to end-users, and overcome the bottleneck of cloud computing. The trend of deploying machine learning (ML) at the network edge to enhance computing applications and services has gained momentum lately, specifically to reduce latency and energy consumed while optimizing the security and management of resources. There is a need for rigorous research efforts oriented towards developing and implementing machine learning algorithms that deliver the best results in terms of speed, accuracy, storage, and security, with low power consumption. This extensive survey presented on the prominent computing paradigms in practice highlights the latest innovations resulting from the fusion between ML and the evolving computing paradigms and discusses the underlying open research challenges and future prospects." @default.
- W4200152024 created "2021-12-31" @default.
- W4200152024 creator A5011127035 @default.
- W4200152024 creator A5025837144 @default.
- W4200152024 creator A5050254224 @default.
- W4200152024 creator A5073849385 @default.
- W4200152024 creator A5091679175 @default.
- W4200152024 date "2021-12-28" @default.
- W4200152024 modified "2023-10-14" @default.
- W4200152024 title "Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies" @default.
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