Intelligent Universal Acceleration Framework and Verification for Edge Cloud Applications

被引:0
|
作者
Mei, Jie [1 ]
Lei, Bo [2 ]
Wang, Xuliang [2 ]
Zhang, Xing [1 ]
Zhao, Qianying [2 ]
机构
[1] Beijing Univ Post & Telecommun, Beijing, Peoples R China
[2] Beijing Res Inst China Telcom, Beijing, Peoples R China
来源
2020 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC WORKSHOPS) | 2020年
基金
国家重点研发计划;
关键词
MEC; edge computing; application acceleration;
D O I
暂无
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
With the development of 5G, the applications impose more diverse and higher performance demands on the infrastructure capability of Edge Cloud. In order to meet the demands, many hardware-based Edge Cloud Application Acceleration schemes have been proposed. However, to ensure the vigorous development of Edge Cloud applications, how to efficiently match and schedule the acceleration capability of edge cloud applications with the diverse acceleration demands of edge cloud applications is one of the indispensable prerequisites. In this paper, an intelligent general acceleration framework for Edge Cloud applications is proposed, which mainly solves the following problems: first, distinguish and model the acceleration demands of applications accurately; second, abstractly model and classify the general acceleration capabilities; third, detect the initial period of application acceleration, and provide intelligent policy scheduling framework according to test results. And the framework achieves accurate matching and scheduling between application acceleration demands and general acceleration capabilities. So, the Intelligent Universal Acceleration Framework can accelerate the application of Edge Cloud accurately, and ensure the efficient utilization of resources. In addition, bandwidth-intensive, face recognition and enterprise VPN gateway are used to validates that the Intelligent Universal Acceleration Framework is helpful to analyze, match and schedule the acceleration demands of applications and the general acceleration capabilities of infrastructure.
引用
收藏
页码:47 / 52
页数:6
相关论文
共 50 条
  • [41] Design Framework and Intelligent In-Vehicle Information System for Sensor-Cloud Platform and Applications
    Zeng, Qingshu
    Duan, Qijun
    Shi, Mingxiang
    He, Xiangjian
    Hassan, Mohammad Mehedi
    IEEE ACCESS, 2020, 8 (08): : 201675 - 201685
  • [42] A Framework with Cloud Integration for CNN Acceleration on FPGA Devices
    Raspa, Niccolo
    Natale, Giuseppe
    Bacis, Marco
    Santambrogio, Marco D.
    2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018), 2018, : 170 - 177
  • [43] BlastFunction: A Full-stack Framework Bringing FPGA Hardware Acceleration to Cloud-native Applications
    Damiani, Andrea
    Fiscaletti, Giorgia
    Bacis, Marco
    Brondolin, Rolando
    Santambrogio, Marco D.
    ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS, 2022, 15 (02)
  • [44] An Attention-Enhanced Edge-Cloud Collaborative Framework for Multi-Task Applications
    Zhang, Zhipeng
    Ma, Wenting
    Li, Feng
    Tang, Renjie
    Wang, Jinlang
    Chen, Wai
    2020 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS AND INTELLIGENCE SYSTEM (IOTAIS), 2021, : 109 - 115
  • [45] DeePar: A Hybrid Device-Edge-Cloud Execution Framework for Mobile Deep Learning Applications
    Huang, Yutao
    Wang, Feng
    Wang, Fangxin
    Liu, Jiangchuan
    IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM 2019 WKSHPS), 2019, : 892 - 897
  • [46] An integrating computing framework based on edge-fog-cloud for internet of healthcare things applications
    Khanh, Quy Vu
    Hoai, Nam Vi
    Van, Anh Dang
    Minh, Quy Nguyen
    INTERNET OF THINGS, 2023, 23
  • [47] Future Edge Cloud and Edge Computing for Internet of Things Applications
    Pan, Jianli
    McElhannon, James
    IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (01): : 439 - 449
  • [48] Booster: An Acceleration-Based Verification Framework for Array Programs
    Alberti, Francesco
    Ghilardi, Silvio
    Sharygina, Natasha
    AUTOMATED TECHNOLOGY FOR VERIFICATION AND ANALYSIS, ATVA 2014, 2014, 8837 : 18 - 23
  • [49] OpenStack Network Acceleration Scheme for Datacenter Intelligent Applications
    Linh Phan
    Liu, Kaikai
    PROCEEDINGS 2018 IEEE 11TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 2018, : 962 - 965
  • [50] An Intelligent Cloud Security System for Critical Applications
    Balusamy, Balamurugan
    Venkatakrishna, P.
    Palani, Gomathi
    Ravikumar, Umamageshwari
    ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY ALGORITHMS IN ENGINEERING SYSTEMS, VOL 2, 2015, 325 : 33 - 40