An artificial neural network-based distributed information-centric network service

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Artificial neural networks (ANN) have been widely used in various areas. As a bottleneck, hardware specification affects the efficiency of an ANN. With the development of distributed computing, distributed ANNs show advantages in dealing with huge data. The network bandwidth is a new bottleneck restricting the performance of distributed ANNs. Information-Centric Networking (ICN) [1], as the Next Generation Network (NGN) solution, has shown merits regarding mobility, security, power consumption and network traffic. In this paper, we remodel the architecture of network service using ANNs. We proposed an ANN-Based Distributed Information-Centric Network Service (ANN based DICNS). The distributed nodes are connected like a neural network. When a client utilizes the DICNS, the data flow from the source to the consumer node like the signal traveling from an input layer to an output layer in a neural network. By using an ICN, our proposal can significantly reduce network consumption, and the named data can help the DICNS effectively manage and classify the data.

    Original languageEnglish
    Title of host publicationProceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017
    PublisherIEEE Computer Society
    Pages453-458
    Number of pages6
    Volume2017-December
    ISBN (Electronic)9781538627679
    DOIs
    Publication statusPublished - 2018 Feb 22
    Event20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017 - Bali, Indonesia
    Duration: 2017 Dec 172017 Dec 20

    Other

    Other20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017
    CountryIndonesia
    CityBali
    Period17/12/1717/12/20

    Fingerprint

    Neural networks
    Next generation networks
    Distributed computer systems
    Electric power utilization
    Specifications
    Hardware
    Bandwidth

    Keywords

    • Artificial neural networks
    • Distributed service
    • Information-centric networking

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Computer Science Applications
    • Human-Computer Interaction

    Cite this

    Wen, Z., & Sato, T. (2018). An artificial neural network-based distributed information-centric network service. In Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017 (Vol. 2017-December, pp. 453-458). IEEE Computer Society. https://doi.org/10.1109/WPMC.2017.8301855

    An artificial neural network-based distributed information-centric network service. / Wen, Zheng; Sato, Takuro.

    Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017. Vol. 2017-December IEEE Computer Society, 2018. p. 453-458.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Wen, Z & Sato, T 2018, An artificial neural network-based distributed information-centric network service. in Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017. vol. 2017-December, IEEE Computer Society, pp. 453-458, 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017, Bali, Indonesia, 17/12/17. https://doi.org/10.1109/WPMC.2017.8301855
    Wen Z, Sato T. An artificial neural network-based distributed information-centric network service. In Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017. Vol. 2017-December. IEEE Computer Society. 2018. p. 453-458 https://doi.org/10.1109/WPMC.2017.8301855
    Wen, Zheng ; Sato, Takuro. / An artificial neural network-based distributed information-centric network service. Proceedings - 20th International Symposium on Wireless Personal Multimedia Communications, WPMC 2017. Vol. 2017-December IEEE Computer Society, 2018. pp. 453-458
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