Scalable Core and Edge Router with Utilization-Based Route Distribution
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Solution Overview
Problem
Existing carrier-grade core and edge routers face scalability issues due to the need for loading all forwarding information on every linecard, which limits growth and consumes critical resources.
Innovation Solution
A distributed, disaggregated cluster (DDC) router architecture that splits the full routing table based on utilization, using recirculation for low-volume routes and dedicated linecards for high-volume routes, allowing for scalable growth and efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all forwarding information is loaded on every linecard, then route lookup completeness is improved, but device complexity and resource consumption increase
Solution Approach 1:
The routing table is segmented into two parts: a local routing table stored on each linecard for fast lookup, and a remote routing table stored in centralized memory for additional routes. This segmentation allows each linecard to maintain only essential routing information while still providing complete route coverage through the distributed architecture.
Solution Approach 2:
The patent introduces a new dimension of route lookup by adding a remote routing table in centralized memory beyond the traditional local linecard storage. This creates a two-layer routing architecture where routes can be found either locally or remotely, expanding the solution space for managing forwarding information.
2Quantity of substance
If routing table size is increased to support more routes, then route handling capability is improved, but scalability is limited by linecard capacity
Solution Approach 1:
The centralized memory structure serves multiple functions: it stores the remote routing table for additional routes, provides centralized management of routing information, and enables dynamic allocation of routing resources. This multi-functional design allows the system to scale beyond the limitations of individual linecard capacity.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, a routing device in a network, the routing device including an ingress/egress linecard; another linecard; a fabric; a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of maintaining a forwarding information base (FIB) for routes through the routing device; moving low-volume routes of the FIB to the another linecard; and moving high-volume routes of the FIB to the ingress/egress linecard, wherein the ingress/egress linecard looks up a route of an incoming data packet, determines whether the incoming data packet bears a high-volume route prefix, forwards the incoming data packet bearing the high-volume route prefix through the fabric and out of the routing device, and sends the incoming data packet bearing a low-volume route prefix through the fabric to the another linecard, and wherein the another linecard forwards the incoming data packet received from the ingress/egress linecard out of the routing device. Other embodiments are disclosed.