Research on resource allocation of vocal music teaching system based on mobile edge computing

被引:24
作者
Sun, Jian [1 ]
机构
[1] Mahasarakham Univ, Dept Mus Coll, Talat, Thailand
关键词
Mobile edge computing; Vocal music; System resources; Resource allocation; Nash equilibrium; SERVICES; CLOUD;
D O I
10.1016/j.comcom.2020.05.016
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
How to allocate vocal teaching system resources plays an important role in improving the performance of vocal teaching systems. With the development of mobile edge computing, the calculation and storage of resource data can be adapted to the operating needs of vocal teaching systems. This study proposes a method of system resource allocation based on power iteration and sets the throughput of the unloading process as an objective function and realizes the optimal allocation of normal power by iterative optimization. At the same time, in view of the low energy efficiency and resource utilization of edge servers, a heterogeneous network based on edge servers is proposed to find the optimal strategy based on ensuring the Nash equilibrium point. In addition, in order to verify the performance of the algorithm in this paper, a comparative experiment is performed by designing simulation experiments. The results show that the method proposed in this paper has certain effects and strong practicability, which can provide theoretical references for subsequent related research.
引用
收藏
页码:342 / 350
页数:9
相关论文
共 28 条
  • [1] [Anonymous], 2018, J COMPUT RES DEV
  • [2] A Decentralized Replica Placement Algorithm for Edge Computing
    Aral, Atakan
    Ovatman, Tolga
    [J]. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2018, 15 (02): : 516 - 529
  • [3] Baresi Luciano., 2017, Empowering Low-Latency Applications Through a Serverless Edge Computing Architecture
  • [4] FAULT-TOLERANT SUBGRAPH FOR SINGLE-SOURCE REACHABILITY: GENERAL AND OPTIMAL
    Baswana, Surender
    Choudhary, Keerti
    Roditty, Liam
    [J]. SIAM JOURNAL ON COMPUTING, 2018, 47 (01) : 80 - 95
  • [5] Human-Enabled Edge Computing: Exploiting the Crowd as a Dynamic Extension of Mobile Edge Computing
    Bellavista, Paolo
    Chessa, Stefano
    Foschini, Luca
    Gioia, Leo
    Girolami, Michele
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (01) : 149 - 155
  • [6] De Assuncao M.D., 2017, J NETW COMPUT APPL
  • [7] The application of mobile edge computing in agricultural water monitoring system
    Fan, D. H.
    Gao, S.
    [J]. 4TH INTERNATIONAL CONFERENCE ON WATER RESOURCE AND ENVIRONMENT (WRE 2018), 2018, 191
  • [8] Application Aware Workload Allocation for Edge Computing-Based IoT
    Fan, Qiang
    Ansari, Nirwan
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (03): : 2146 - 2153
  • [9] Degree-constrained minimum spanning tree problem of uncertain random network
    Gao, Xin
    Jia, Lifen
    Kar, Samarjit
    [J]. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2017, 8 (05) : 747 - 757
  • [10] Virtual Network Embedding for Collaborative Edge Computing in Optical-Wireless Networks
    Gong, Xiaoxue
    Guo, Lei
    Shen, Gangxiang
    Tian, Guoda
    [J]. JOURNAL OF LIGHTWAVE TECHNOLOGY, 2017, 35 (18) : 3980 - 3990