A routing method with adaptively adjusting memory information based on local routing history

Area of Science:

• Computer Science
• Network Engineering
• Information Theory

Background:

• Packet-switched networks require efficient routing for high-speed data transmission.
• Existing routing methods with memory information struggle with specific network topologies like those with local triangular connections.
• Congestion in large packet flows remains a significant challenge in communication networks.

Purpose of the Study:

• To enhance packet routing performance in diverse communication network topologies.
• To overcome the limitations of existing memory-based routing methods in complex network structures.
• To develop a more robust and efficient routing strategy for future high-speed information networks.

Main Methods:

• Incorporated betweenness centrality of nodes to identify critical paths and potential congestion points.
• Developed an adaptive routing strategy that utilizes only local network information.
• Enhanced conventional communication network models with the proposed routing approach.

Main Results:

• The proposed routing method successfully avoids congested nodes in various network topologies.
• Demonstrated improved transmission completion rates and efficiency compared to previous methods.
• Effectively utilized memory information for adaptive path selection.

Conclusions:

• The enhanced routing method, leveraging betweenness centrality and local information, offers superior performance across different network structures.
• This approach effectively mitigates congestion and improves data flow efficiency in packet-switched networks.
• The findings contribute to building more resilient and high-speed communication networks.