Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks

被引:7
|
作者
Baccour, Emna [1 ]
Allahham, Mhd Saria [2 ,3 ]
Erbad, Aiman [1 ]
Mohamed, Amr [3 ]
Hussein, Ahmed Refaey [4 ]
Hamdi, Mounir [1 ]
机构
[1] Hamad Bin Khalifa Univ, Qatar Fdn, Ar Rayyan, Qatar
[2] Queens Univ, Kingston, ON, Canada
[3] Qatar Univ, Doha, Qatar
[4] Univ Guelph, Guelph, ON, Canada
关键词
6G mobile communication; Knowledge engineering; Costs; Prototypes; Standardization; Security; Resource management;
D O I
10.1109/MCOM.001.2200508
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The vision of the upcoming 6G technologies, characterized by ultra-dense networks, low latency, and fast data rate, is to support pervasive artificial intelligence (PAI) using zero touch solutions enabling self-X (e.g., self-configuration, self-monitoring, and self-healing) services. However, the research on 6G is still in its infancy, and only the first steps have been taken to conceptualize its design, investigate its implementation, and plan for use cases. Toward this end, academia and industry communities have gradually shifted from theoretical studies of AI distribution to real-world deployment and standardization. Still, designing an end-to-end framework that systematizes the AI distribution by allowing easier access to the service using a third-party application assisted by zero touch service provisioning has not been well explored. In this context, we introduce a novel platform architecture to deploy a zero touch PAI as a service (PAlaaS) in 6G networks supported by a blockchain-based smart system. This platform aims to standardize the PAI at all levels of the architecture and unify the interfaces in order to facilitate service deployment across application and infrastructure domains, relieve users' worries about cost, security, and resource allocation, and at the same time respect the 6G's stringent performance requirements. As a proof of concept, we present a federated-learning-as-a-service use case where we evaluate the ability of our proposed system to self-optimize and self-adapt to the dynamics of 6G networks in addition to minimizing the users' perceived costs.
引用
下载
收藏
页码:110 / 116
页数:7
相关论文
共 50 条
  • [1] Workshop on Pervasive Network Intelligence for 6G Networks (PerAI-6G)
    Zhang, Ning
    Han, Tao
    INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops, 2022,
  • [2] The Role of Edge Artificial Intelligence in 6G Networks
    Kitanov, Stojan
    Nikolikj, Vladimir
    2022 57TH INTERNATIONAL SCIENTIFIC CONFERENCE ON INFORMATION, COMMUNICATION AND ENERGY SYSTEMS AND TECHNOLOGIES (ICEST), 2022, : 33 - 36
  • [3] Artificial Intelligence for 6G Networks Technology Advancement and Standardization
    Shehzad, Muhammad K.
    Rose, Luca
    Butt, M. Majid
    Kovacs, Istvan Z.
    Assaad, Mohamed
    Guizani, Mohsen
    IEEE VEHICULAR TECHNOLOGY MAGAZINE, 2022, 17 (03): : 16 - 25
  • [4] Artificial-Intelligence-Enabled Intelligent 6G Networks
    Yang, Helin
    Alphones, Arokiaswami
    Xiong, Zehui
    Niyato, Dusit
    Zhao, Jun
    Wu, Kaishun
    IEEE NETWORK, 2020, 34 (06): : 272 - 280
  • [5] Enabling 6G Security: The Synergy of Zero Trust Architecture and Artificial Intelligence
    Sedjelmaci, Hichem
    Tourki, Kamel
    Ansari, Nirwan
    IEEE NETWORK, 2024, 38 (03): : 171 - 177
  • [6] Semi-Federated Learning: An Integrated Framework for Pervasive Intelligence in 6G Networks
    Zheng, Jingheng
    Ni, Wanli
    Tian, Hui
    Gunduz, Deniz
    Quek, Tony Q. S.
    IEEE INFOCOM 2022 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2022,
  • [7] Artificial Intelligence in 6G Wireless Networks: Opportunities, Applications, and Challenges
    Alhammadi, Abdulraqeb
    Shayea, Ibraheem
    El-Saleh, Ayman A.
    Azmi, Marwan Hadri
    Ismail, Zool Hilmi
    Kouhalvandi, Lida
    Saad, Sawan Ali
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2024, 2024
  • [8] Edge intelligence for 6G networks
    Zheng, Haifeng
    Gao, Lin
    Chen, Zhiyong
    Xiao, Liang
    CHINA COMMUNICATIONS, 2022, 19 (08)
  • [9] Edge Intelligence for 6G Networks
    Haifeng Zheng
    Lin Gao
    Zhiyong Chen
    Liang Xiao
    China Communications, 2022, 19 (08) : 3 - 5
  • [10] Artificial intelligence in 5G and 6G
    Laselva, Sarah
    Electronics World, 2024, 129 (2033): : 16 - 17