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This study introduces two schemes for uplink data caching in distributed Beyond Fifth Generation (B5G) Content-Centric Networks (CCNs). These methods enhance efficiency by reducing duplicate content and optimizing cache space, improving overall network performance.

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Telecommunications

Background:

  • Content-centric networks (CCNs) increase data traffic, leading to congestion in Beyond Fifth Generation (B5G) networks.
  • Uplink data caching in distributed B5G scenarios faces challenges like duplicate content and unawareness of cached data.
  • Optimizing distributed caching for popular content is crucial for efficient space utilization.

Purpose of the Study:

  • To propose novel schemes for uplink transmission in distributed B5G CCNs.
  • To address challenges of duplicate content matching and efficient space utilization in distributed caches.
  • To enhance energy and spectral efficiency while improving content delivery.

Main Methods:

  • Developed two schemes for uplink transmission in distributed B5G CCNs.
  • Scheme 1: Focuses on content matching to eliminate duplicate cached content.
  • Scheme 2: Redistributes unique cached content based on available space and content size.

Main Results:

  • Proposed schemes significantly outperform existing methods.
  • Cache hit ratio improved by 29.17%, cache hit probability by 74.89%, cache efficiency by 24.17%, and diversity by 80%.
  • Access network throughput, Spectrum Efficiency (SE), and Energy Efficiency (EE) improved by 17.78%, 18%, and 78%, respectively. Sidehaul and backhaul links of Small Base Stations (SBSs) also showed improved EE and SE.

Conclusions:

  • The proposed uplink caching schemes effectively reduce duplicate content and optimize space in distributed B5G CCNs.
  • Significant improvements in cache performance, network efficiency (SE and EE), and content delivery were achieved.
  • These advancements are vital for managing data transmission challenges in future wireless networks.