IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v17y2025i1p11-d1558477.html
   My bibliography  Save this article

Cache Aging with Learning (CAL): A Freshness-Based Data Caching Method for Information-Centric Networking on the Internet of Things (IoT)

Author

Listed:
  • Nemat Hazrati

    (Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz 5157944533, Iran)

  • Sajjad Pirahesh

    (Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz 5157944533, Iran)

  • Bahman Arasteh

    (Department of Software Engineering, Faculty of Engineering and Natural Science, Istinye University, Istanbul 34460, Türkiye
    Department of Computer Science, Khazar University, Baku AZ1096, Azerbaijan
    Applied Science Research Center, Applied Science Private University, Amman 11937, Jordan)

  • Seyed Salar Sefati

    (Department of Software Engineering, Faculty of Engineering and Natural Science, Istinye University, Istanbul 34460, Türkiye
    Faculty of Electronics, Telecommunications and Information Technology, National University for Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania)

  • Octavian Fratu

    (Faculty of Electronics, Telecommunications and Information Technology, National University for Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 050044 Bucharest, Romania)

  • Simona Halunga

    (Faculty of Electronics, Telecommunications and Information Technology, National University for Science and Technology POLITEHNICA Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 050044 Bucharest, Romania)

Abstract

Information-centric networking (ICN) changes the way data are accessed by focusing on the content rather than the location of devices. In this model, each piece of data has a unique name, making it accessible directly by name. This approach suits the Internet of Things (IoT), where data generation and real-time processing are fundamental. Traditional host-based communication methods are less efficient for the IoT, making ICN a better fit. A key advantage of ICN is in-network caching, which temporarily stores data across various points in the network. This caching improves data access speed, minimizes retrieval time, and reduces overall network traffic by making frequently accessed data readily available. However, IoT systems involve constantly updating data, which requires managing data freshness while also ensuring their validity and processing accuracy. The interactions with cached data, such as updates, validations, and replacements, are crucial in optimizing system performance. This research introduces an ICN-IoT method to manage and process data freshness in ICN for the IoT. It optimizes network traffic by sharing only the most current and valid data, reducing unnecessary transfers. Routers in this model calculate data freshness, assess its validity, and perform cache updates based on these metrics. Simulation results across four models show that this method enhances cache hit ratios, reduces traffic load, and improves retrieval delays, outperforming similar methods. The proposed method uses an artificial neural network to make predictions. These predictions closely match the actual values, with a low error margin of 0.0121. This precision highlights its effectiveness in maintaining data currentness and validity while reducing network overhead.

Suggested Citation

  • Nemat Hazrati & Sajjad Pirahesh & Bahman Arasteh & Seyed Salar Sefati & Octavian Fratu & Simona Halunga, 2025. "Cache Aging with Learning (CAL): A Freshness-Based Data Caching Method for Information-Centric Networking on the Internet of Things (IoT)," Future Internet, MDPI, vol. 17(1), pages 1-24, January.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:1:p:11-:d:1558477
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/17/1/11/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/17/1/11/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shrisha H. S. & Uma Boregowda, 2022. "Quality-of-Service-Linked Privileged Content-Caching Mechanism for Named Data Networks," Future Internet, MDPI, vol. 14(5), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:17:y:2025:i:1:p:11-:d:1558477. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.