A Novel Middleware for Efficiently Implementing Complex Cloud-Native SLOs

Pusztai, Thomas; Morichetta, Andrea; Pujol, Víctor Casamayor; Dustdar, Schahram; Nastić, Stefan; Ding, Xiaoning; Vij, Deepak; Xiong, Ying

doi:10.1109/cloud53861.2021.00055

Cited by 20 publications

(1 citation statement)

References 17 publications

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“…Customers are more concerned about their privacy and want to know how and where their data is acquired and maintained. After completing the app's authentication procedure, a slew of businesses serve their clients by offering applications with AI-enabled tailored features [106]. These aid users in protecting their personal information.…”

Section: Edge Computingmentioning

confidence: 99%

AI for Next Generation Computing: Emerging Trends and Future Directions

Gill,

Xu,

Ottaviani

et al. 2022

Preprint

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Autonomic computing investigates how systems can achieve (user) specified "control" outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and inter-dependent control loops. Despite research into autonomic models for managing computer resources, ranging from individual resources (e.g., web servers) to a resource ensemble (e.g., multiple resources within a data center), research into integrating Artificial Intelligence (AI) and Machine Learning (ML) to improve resource autonomy and performance at scale continues to be a fundamental challenge. The integration of AI/ML to achieve such autonomic and self-management of systems can be achieved at different levels of granularity, from full to human-in-the-loop automation. In this article, leading academics, researchers, practitioners, engineers, and scientists in the fields of cloud computing, AI/ML, and quantum computing join to discuss current research and potential future directions for these fields. Further, we discuss challenges and opportunities for leveraging AI and ML in next generation computing for emerging computing paradigms, including cloud, fog, edge, serverless and quantum computing environments.

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Section: Edge Computingmentioning

confidence: 99%