Software-defined Software: A Perspective of Machine Learning-based Software Production

被引:4
|
作者
Lee, Rubao [1 ]
Wang, Hao [1 ]
Zhang, Xiaodong [1 ]
机构
[1] Ohio State Univ, Dept Comp Sci & Engn, Columbus, OH 43210 USA
基金
美国国家科学基金会;
关键词
DEEP; GAME; GO;
D O I
10.1109/ICDCS.2018.00126
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As the Moore's Law is ending, and increasingly high demand of software development continues in the human society, we are facing two serious challenges in the computing field. First, the general-purpose computing ecosystem that has been developed for more than 50 years will have to be changed by including many diverse devices for various specialties in high performance. Second, human-based software development is not sustainable to respond the requests from all the fields in the society. We envision that we will enter a time of developing high quality software by machines, and we name this as Software-defined Software (SDS). In this paper, we will elaborate our vision, the goals and its roadmap.
引用
收藏
页码:1270 / 1275
页数:6
相关论文
共 50 条
  • [1] Software-Defined IoT with Machine Learning-Based Enhanced Security
    Husnain, Ali
    Nguyen, Chau
    Le, Ngoc Thuy
    [J]. 2023 28TH ASIA PACIFIC CONFERENCE ON COMMUNICATIONS, APCC 2023, 2023, : 430 - 435
  • [2] A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks
    Latif, Zohaib
    Umer, Qasim
    Lee, Choonhwa
    Sharif, Kashif
    Li, Fan
    Biswas, Sujit
    [J]. SENSORS, 2022, 22 (21)
  • [3] Machine Learning-Based Routing and Wavelength Assignment in Software-Defined Optical Networks
    Martin, Ignacio
    Troia, Sebastian
    Alberto Hernandez, Jose
    Rodriguez, Alberto
    Musumeci, Francesco
    Maier, Guido
    Alvizu, Rodolfo
    Gonzalez de Dios, Oscar
    [J]. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2019, 16 (03): : 871 - 883
  • [4] Machine learning-based IDS for software-defined 5G network
    Li, Jiaqi
    Zhao, Zhifeng
    Li, Rongpeng
    [J]. IET NETWORKS, 2018, 7 (02) : 53 - 60
  • [5] Machine Learning-Based Botnet Detection in Software-Defined Network: A Systematic Review
    Shinan, Khlood
    Alsubhi, Khalid
    Alzahrani, Ahmed
    Ashraf, Muhammad Usman
    [J]. SYMMETRY-BASEL, 2021, 13 (05):
  • [6] Deep Reinforcement Learning-Based Routing on Software-Defined Networks
    Kim, Gyungmin
    Kim, Yohan
    Lim, Hyuk
    [J]. IEEE ACCESS, 2022, 10 : 18121 - 18133
  • [7] A New Machine Learning-based Collaborative DDoS Mitigation Mechanism in Software-Defined Network
    Mohammed, Saif Saad
    Hussain, Rasheed
    Senko, Oleg
    Bimaganbetov, Bagdat
    Lee, JooYoung
    Hussain, Fatima
    Kerrache, Chaker Abdelaziz
    Barka, Ezedin
    Bhuiyan, Md Zakirul Alam
    [J]. 2018 14TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB 2018), 2018,
  • [8] Machine learning-based centralized link coding attack detection in software-defined network
    Wang, Hongyuan
    [J]. WIRELESS NETWORKS, 2023,
  • [9] Machine Learning-Based Multipath Routing for Software Defined Networks
    Mohamad Khattar Awad
    Marwa Hassan Hafez Ahmed
    Ali F. Almutairi
    Imtiaz Ahmad
    [J]. Journal of Network and Systems Management, 2021, 29
  • [10] Machine Learning-Based Multipath Routing for Software Defined Networks
    Awad, Mohamad Khattar
    Ahmed, Marwa Hassan Hafez
    Almutairi, Ali F.
    Ahmad, Imtiaz
    [J]. JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT, 2021, 29 (02)