Computing Power Network: A Survey

被引:5
作者
Sun, Yukun [1 ]
Lei, Bo [2 ]
Liu, Junlin [1 ]
Huang, Haonan [1 ]
Zhang, Xing [1 ]
Peng, Jing [3 ]
Wang, Wenbo [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China
[2] Res Inst China Telecom Co Ltd, Beijing 102209, Peoples R China
[3] Beijing Branch China Telecom Co Ltd, Beijing 100032, Peoples R China
基金
美国国家科学基金会;
关键词
computing power modeling; computing; power network; computing power scheduling; infor- mation awareness; network forwarding; RESOURCE-ALLOCATION; EDGE; COMPUTATION; ARCHITECTURE; AWARE; PREDICTION; CONSENSUS; INTERNET; SCHEMES; DOCKER;
D O I
10.23919/JCC.ja.2021-0776
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
With the rapid development of cloud computing, edge computing, and smart devices, computing power resources indicate a trend of ubiquitous deployment. The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect. To overcome these problems and improve network efficiency, a new network computing paradigm is proposed, i.e., Computing Power Network (CPN). Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly. In this survey, we make an exhaustive review on the state-of-the-art research efforts on computing power network. We first give an overview of computing power network, including definition, architecture, and advantages. Next, a comprehensive elaboration of issues on computing power modeling, information awareness and announcement, resource allocation, network forwarding, computing power transaction platform and resource orchestration platform is presented. The computing power network testbed is built and evaluated. The applications and use cases in computing power network are discussed. Then, the key enabling technologies for computing power network are introduced. Finally, open challenges and future research directions are presented as well.
引用
收藏
页码:109 / 145
页数:37
相关论文
共 109 条
  • [1] Docker Image Sharing in Distributed Fog Infrastructures
    Ahmed, Arif
    Pierre, Guillaume
    [J]. 11TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM 2019), 2019, : 135 - 142
  • [2] Delay-Aware and Energy-Efficient Computation Offloading in Mobile-Edge Computing Using Deep Reinforcement Learning
    Ale, Laha
    Zhang, Ning
    Fang, Xiaojie
    Chen, Xianfu
    Wu, Shaohua
    Li, Longzhuang
    [J]. IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING, 2021, 7 (03) : 881 - 892
  • [3] [Anonymous], 2012, WHITE PAPER NVIDIA G
  • [4] [Anonymous], 2017, SG11 ITUT
  • [5] [Anonymous], 2021, SG13 ITUT
  • [6] [Anonymous], 2019, WHITE PAPER COMPUTIN
  • [7] [Anonymous], 2020, SG13 ITUT
  • [8] Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems Under Resource Uncertainty
    Apostolopoulos, Pavlos Athanasios
    Fragkos, Georgios
    Tsiropoulou, Eirini Eleni
    Papavassiliou, Symeon
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (01) : 175 - 190
  • [9] A Taxonomy and Survey of Edge Cloud Computing for Intelligent Transportation Systems and Connected Vehicles
    Arthurs, Peter
    Gillam, Lee
    Krause, Paul
    Wang, Ning
    Halder, Kaushik
    Mouzakitis, Alexandros
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (07) : 6206 - 6221
  • [10] Distributed SDN Control: Survey, Taxonomy, and Challenges
    Bannour, Fetia
    Souihi, Sami
    Mellouk, Abdelhamid
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (01): : 333 - 354