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Efficient Network Slicing with SDN and Heuristic Algorithm for Low Latency Services in 5G/B5G Networks.

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Summary

This study introduces an enhanced A* algorithm for 5G backhaul network slicing, optimizing paths for low-latency services. The novel approach significantly reduces processing time and ensures ultra-reliable low-latency communication (URLLC).

Keywords:
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Area of Science:

  • Computer Science
  • Telecommunications Engineering

Background:

  • 5G backhaul networks require efficient solutions for ultra-reliable low-latency communication (URLLC).
  • Existing routing algorithms may not adequately address stringent latency requirements for critical services.

Purpose of the Study:

  • To develop and evaluate a novel network slicing approach for 5G backhaul networks.
  • To improve path computation efficiency and real-time adaptability for low-latency services.

Main Methods:

  • A modified A* algorithm was developed, incorporating Quality of Service (QoS) parameters into a composite metric.
  • The algorithm was integrated into a Software-Defined Networking (SDN) Path Computation Element (PCE).
  • Real-time congestion monitoring and a precalculated heuristic function were employed.

Main Results:

  • The modified A* algorithm demonstrated significant processing time reductions (order of magnitude) compared to Dijkstra's algorithm, especially in complex networks.
  • The algorithm successfully adjusted paths in real-time to maintain low latency, preventing packet delay thresholds from being exceeded.
  • End-to-end measurements validated the algorithm's effectiveness in traffic differentiation based on latency requirements.

Conclusions:

  • The proposed modified A* algorithm offers an efficient and effective solution for network slicing in 5G backhaul.
  • This approach enables the achievement of URLLC by optimizing path computation and managing network congestion in real-time.