Gateway Router WAN Optimization via Stream Aggregation
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Solution Overview
Problem
Existing solutions for optimizing data transmission over wide area networks (WAN) are inflexible, costly, and inefficient, leading to data duplication and synchronization issues across multiple cloud regions.
Innovation Solution
A method for WAN optimization that involves a gateway router deployed in a public cloud, which aggregates multiple data streams from edge routers, performs traffic redundancy elimination (TRE), and compresses the data streams to produce a single, optimized outbound stream for forwarding to a centralized datacenter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If multiple unoptimized data streams are sent individually from multiple routers to the centralized datacenter, then data transmission is performed, but bandwidth usage is excessive and transmission costs are high
Solution Approach 1:
The patent merges multiple data streams from different routers into a single aggregated data stream at the gateway router. This consolidation reduces the number of separate transmissions across the WAN, thereby decreasing total bandwidth consumption and transmission costs while maintaining data transmission productivity through efficient stream combining and redundancy elimination.
Solution Approach 2:
The gateway router performs multiple functions including stream aggregation, redundancy elimination, and compression in a single device. This multi-functional approach optimizes bandwidth usage by handling multiple optimization tasks centrally rather than requiring separate systems for each function.
2Adaptability or versatility
If data is moved to a central data-warehouse or few data-lakes with compute allocated at the same place, then data centralization is achieved, but the solution is inflexible, slow, and expensive with indiscriminate data duplication and synchronization
Solution Approach 1:
The patent extracts redundant data segments from the aggregated streams using traffic redundancy elimination (TRE) before centralization. By removing duplicates at the gateway level, the system reduces the quantity of data that needs to be stored and synchronized at the centralized datacenter, thereby decreasing data duplication while maintaining flexibility and speed.
Solution Approach 2:
The gateway router performs preliminary optimization operations including aggregation, redundancy elimination, and compression before data is sent to the centralized datacenter. This pre-processing reduces the burden on the centralized system, enabling faster and more flexible data handling while minimizing duplication.
3Loss of energy
If multiple unoptimized data streams are transmitted, then data from multiple sites is delivered, but transmission costs are high
Solution Approach 1:
The gateway router acts as an intermediary between multiple edge routers and the centralized datacenter. It performs WAN optimization operations including aggregation and redundancy elimination, thereby reducing transmission costs without requiring complex optimizations at each edge router or at the centralized datacenter.
Solution Approach 2:
The system performs self-service optimization at the gateway level, where the gateway automatically aggregates streams, eliminates redundancy, and compresses data without requiring manual intervention or complex external systems. This reduces transmission costs while keeping the optimization mechanism relatively simple and self-contained.
Data Source
AI summary
Some embodiments of the invention provide a method for WAN (wide area network) optimization for a WAN that connects multiple sites, each of which has at least one router. At a gateway router deployed to a public cloud, the method receives from at least two routers at least two sites, multiple data streams destined for a particular centralized datacenter. The method performs a WAN optimization operation to aggregate the multiple streams into one outbound stream that is WAN optimized for forwarding to the particular centralized datacenter. The method then forwards the WAN-optimized data stream to the particular centralized datacenter.