Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies

Sensors

Dakshanamoorthy Ravindran¹  Nancy A Angel¹  Yuh-Chung Hu²  Kathiravan Srinivasan³  P M Durai Raj Vincent⁴ 

[1] Department of Computer Science, St. Joseph’s College (Autonomous), Bharathidasan University, Tiruchirappalli 620002, India;Department of Mechanical and Electromechanical Engineering, National ILan University, Yilan 26047, Taiwan;School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, India;School of Information Technology and Engineering, Vellore Institute of Technology, Vellore 632014, India;

关键词: cloud computing;    edge computing;    fog computing;    internet-of-things;    machine learning;   

DOI  :  10.3390/s22010196

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown