AI for next generation computing: Emerging trends and future directions

被引:306
作者
Gill, Sukhpal Singh [1 ]
Xu, Minxian [2 ]
Ottaviani, Carlo [3 ,4 ]
Patros, Panos [5 ]
Bahsoon, Rami [6 ]
Shaghaghi, Arash [7 ]
Golec, Muhammed [1 ]
Stankovski, Vlado [8 ]
Wu, Huaming [9 ]
Abraham, Ajith [10 ,11 ]
Singh, Manmeet [12 ,13 ]
Mehta, Harshit [14 ,15 ]
Ghosh, Soumya K. [16 ]
Baker, Thar [17 ]
Parlikad, Ajith Kumar [18 ]
Lutfiyya, Hanan [19 ]
Kanhere, Salil S. [20 ]
Sakellariou, Rizos [21 ]
Dustdar, Schahram [22 ]
Rana, Omer [23 ]
Brandic, Ivona [24 ]
Uhlig, Steve [1 ]
机构
[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
[2] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
[3] Univ York, Dept Comp Sci, York, N Yorkshire, England
[4] Univ York, York Ctr Quantum Technol, York, N Yorkshire, England
[5] Univ Waikato, Dept Software Engn, Hamilton, New Zealand
[6] Univ Birmingham, Sch Comp Sci, Birmingham, W Midlands, England
[7] RMIT Univ, Dept Informat Syst & Business Analyt, Melbourne, Vic, Australia
[8] Univ Ljubljana, Fac Comp & Informat Sci, Ljubljana, Slovenia
[9] Tianjin Univ, Ctr Appl Math, Tianjin, Peoples R China
[10] Machine Intelligence Res Labs, Auburn, WA USA
[11] Innopolis Univ, Ctr Artificial Intelligence, Innopolis, Russia
[12] Univ Texas Austin, Jackson Sch Geosci, Austin, TX 78712 USA
[13] Indian Inst Trop Meteorol, Ctr Climate Change Res, Pune, Maharashtra, India
[14] Univ Texas Austin, Cockrell Sch Engn Walker, Dept Mech Engn, Austin, TX 78712 USA
[15] Dell Technol, Austin, TX USA
[16] Indian Inst Technol, Dept Comp Sci & Engn, Kharagpur, W Bengal, India
[17] Univ Sharjah, Dept Comp Sci, Sharjah, U Arab Emirates
[18] Univ Cambridge, Inst Mfg, Dept Engn, Cambridge, England
[19] Univ Western Ontario, Dept Comp Sci, London, ON, Canada
[20] Univ New South Wales UNSW, Sch Comp Sci & Engn, Sydney, NSW, Australia
[21] Univ Manchester, Dept Comp Sci, Oxford Rd, Manchester, Lancs, England
[22] Vienna Univ Technol, Distributed Syst Grp, Vienna, Austria
[23] Cardiff Univ, Sch Comp Sci & Informat, Cardiff, Wales
[24] Vienna Univ Technol, Fac Informat, Vienna, Austria
基金
中国国家自然科学基金;
关键词
Next generation computing; Artificial intelligence; Cloud computing; Fog computing; Edge computing; Serverless computing; Quantum computing; Machine learning; ARTIFICIAL-INTELLIGENCE; MIGRATION SCHEMES; DATA ANALYTICS; INTERNET; MANAGEMENT; THINGS; SYSTEM; IOT; OPTIMIZATION; ARCHITECTURE;
D O I
10.1016/j.iot.2022.100514
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 centre), 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.
引用
收藏
页数:34
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