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

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.