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Intelligent Holographic Computing Fusion Network for IoT Consumer Technology

Haewon ByeonConvergence Department, Korea University of Technology and Education, Cheonan, South KoreaMohammed KhalafDepartment of Computer Science, College of Science, University of Al-Maarif, Ramadi, IraqJanjhyam Venkata Naga RameshDepartment of Computer Science and Engineering, Graphic Era Hill University, Dehradun, IndiaAnkur ChaudharyDepartment of Information Technology, Noida Institute of Engineering and Technology, Greater Noida, IndiaTariq Ahamed AhangerDepartment of Management Information Systems, CoBA, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi ArabiaK. B. V. Brahma RaoDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, IndiaDivya NimmaDepartment of Computational Science, The University of Southern Mississippi, Hattiesburg, MS, USANavruzbek ShavkatovDepartment of Corporate Finance and Securities, Tashkent State University of Economics, Tashkent, UzbekistanRupesh GuptaCentre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, India
ABI

Аннотация

With the rapid evolution of holographic technology, its integration into IoT-based consumer electronics is revolutionizing user experiences in areas such as smart entertainment systems, immersive education platforms, and remote healthcare solutions. However, existing network resource scheduling approaches fall short of meeting the stringent requirements of holographic communication, which demands ultra-high bandwidth, low latency, and synchronized data transmission. To address these challenges, this paper introduces an intelligent computing-integrated network architecture tailored for consumer electronics, leveraging in-network computing to dynamically process and optimize data during transmission. We propose a novel identification mapping framework based on service, resource chain, network function, and network component identifiers to enable adaptive and efficient scheduling of holographic services across heterogeneous resources, including compute, storage, and forwarding elements. Building on this, an intelligent computing-integrated network system is developed to support seamless holographic communication in IoT consumer electronics. Experimental evaluations reveal that the proposed system reduces network bandwidth consumption by up to 60% and transmission latency by 45%, outperforming conventional edge computing approaches and significantly enhancing the responsiveness and efficiency of consumer electronic devices.

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