Efficient and Adaptive P3FA Forwarding Using Popularity-Based Egress Clustering

Addressing the issue of conventional forwarding techniques experiencing slow lookup speeds when managing substantial and intricate forwarding tables, which consequently results in increased latency, inefficiency, and suboptimal network resource utilization, this paper proposes a novel forwarding scheme called Egress Clustered P3FA, employing a graph-theoretic clustering algorithm for egress nodes organization based on their popularity. By partitioning the forwarding table into distinct groups, the graph-theoretic clustering algorithm effectively reduces the copious forwarding entries to a smaller and more manageable table. We exploit the correlations among ports to identify output port clusters exhibiting high and low interrelatedness. Simulation results demonstrate that our proposed method significantly enhances the forwarding lookup speeds and optimizes network resource utilization. With the implementation of Egress Clustered P3FA, a more efficient and stable network transmission is achieved, laying the foundation for future applications and scenarios demanding greater network loads.