Aggregation Circuit for Ethernet Switch Fabric Data Stream Merging
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Solution Overview
Problem
High-performance switch fabrics and packet processors in Gigabit Ethernet networks often operate at a fraction of their capacity due to uneven data processing loads, leading to inefficient usage of processing capacity.
Innovation Solution
A method and apparatus that aggregate multiple input data streams from first processors into a single data stream for a second processor, utilizing ingress data ports, an aggregation module, memory, and an output data port, where the aggregation module analyzes and combines data streams based on priority factors to optimize data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If switch fabrics and packet processors operate at fraction of capacity to handle uneven data processing loads, then system stability is maintained, but processing capacity utilization deteriorates
Solution Approach 1:
The patent combines multiple input data streams from different processors into a single aggregated data stream. The aggregation module merges data packets from multiple sources, applying priority factors to determine which packets are transmitted first. This consolidation allows the switch fabric to operate at full capacity by continuously processing aggregated traffic without idle periods caused by uneven individual stream patterns.
2Productivity
If multiple data streams are processed separately, then data processing reliability is maintained, but processing efficiency deteriorates
Solution Approach 1:
Multiple separate data streams are merged into a single aggregated stream through the aggregation module. This combining operation improves efficiency by allowing the switch fabric to operate continuously at full capacity. Priority factors embedded in each packet maintain reliability by ensuring critical data packets are processed first, even within the aggregated stream.
Solution Approach 2:
The patent changes the parameter of data stream organization from multiple separate streams to a single aggregated stream. By transforming the data flow structure and applying priority-based scheduling, the system achieves both high processing efficiency and maintained reliability through optimized packet handling sequences.
3Productivity
If switch fabric capacity is increased to handle peak loads, then processing capacity is improved, but cost and complexity deteriorate
Solution Approach 1:
The aggregation module performs self-service by automatically analyzing priority factors and scheduling packets without external intervention. This intelligent self-management allows the existing switch fabric to operate at full capacity through software-based prioritization rather than requiring additional hardware resources, thereby avoiding increased system complexity.
4Productivity
If data streams are aggregated with priority factors, then processing efficiency is improved, but device complexity deteriorates
Solution Approach 1:
Priority factors are determined and embedded in packet headers before aggregation occurs. This preliminary action allows the aggregation module to simply read and act on pre-computed priority information rather than making complex real-time decisions, thereby improving processing efficiency while minimizing the complexity of the aggregation circuit itself.
Data Source
AI summary
A method and apparatus aggregate a plurality of input data streams from first processors into one data stream for a second processor, the circuit and the first and second processors being provided on an electronic circuit substrate. The aggregation circuit includes (a) a plurality of ingress data ports, each ingress data port adapted to receive an input data stream from a corresponding first processor, each input data stream formed of ingress data packets, each ingress data packet including priority factors coded therein, (b) an aggregation module coupled to the ingress data ports, adapted to analyze and combine the plurality of input data steams into one aggregated data stream in response to the priority factors, (c) a memory coupled to the aggregation module, adapted to store analyzed data packets, and (d) an output data port coupled to the aggregation module, adapted to output the aggregated data stream to the second processor.