Data communication switches interconnect network devices residing in different network domains. Such switches typically include a plurality of switching modules for switching data traffic between external network devices and a centralized management module for configuring the switching modules. Part of the switching module configuration is “source learning.” Source learning is the process of dynamically learning associations between ports and the addresses of network devices they support by reviewing source addresses in inbound packets. By making such address-port associations, packets can be advantageously forwarded only on the ports of the switch supporting packet destinations rather than being “flooded” on all ports.
In a conventional source learning process, source addresses in packets are reviewed by a switching module upon ingress and unknown source addresses are submitted to the source learning function resident on a centralized management module for processing. The management module configures the address-port association on the switching modules such that future inbound packets destined to that address can be forwarded without unnecessary flooding.
While the source learning process has resulted in bandwidth savings in the form of reduced flooding, such savings have come at a price. Reliance on a centralized management entity for source learning has required a special internal protocol for flagging packets requiring source learning for capture by the management entity and has caused bottlenecks at the management module when many packets requiring source learning arrive at different switching modules within a short period of time.