Gateway Router WAN Optimization with Homomorphic Encryption
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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 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 operational costs increase
Solution Approach 1:
The gateway router aggregates multiple data streams from different edge routers into a single optimized outbound stream. This merging process combines redundant data paths and eliminates duplicate transmissions, thereby reducing overall bandwidth consumption while improving transmission efficiency through centralized optimization.
Solution Approach 2:
The gateway router performs multiple functions including aggregation, redundancy elimination, compression, and encryption on a unified data stream. This multi-functional approach allows a single optimized stream to serve multiple original sources, reducing bandwidth usage while maintaining the productivity of data transmission to the centralized datacenter.
2Stability of the object's composition
If data is moved to a central data-warehouse or few data-lakes with centralized compute, then data synchronization is achieved, but data duplication increases and synchronization becomes slow
Solution Approach 1:
The Traffic Redundancy Elimination (TRE) operation extracts and identifies duplicate data segments across multiple incoming streams. By detecting and removing redundant segments before forwarding to the centralized datacenter, the system achieves data synchronization without creating unnecessary duplications, thereby reducing the quantity of transmitted data while maintaining synchronization stability.
Solution Approach 2:
The gateway router performs aggregation, redundancy elimination, and compression operations before the data reaches the centralized datacenter. This preliminary optimization prevents data duplication from occurring in the first place, rather than having to manage and synchronize duplicates afterward, thereby reducing data duplication while maintaining synchronization.
3Reliability
If encryption is applied to data streams for security, then data security is improved, but WAN optimization operations become more difficult to perform
Solution Approach 1:
The gateway router acts as an intermediary that performs WAN optimization operations on encrypted data streams without requiring decryption. By operating directly on the ciphertext, the gateway maintains data security while performing aggregation, redundancy elimination, and compression, thereby avoiding the complexity of decrypting and re-encrypting data while still achieving optimization.
Solution Approach 2:
The system replaces the traditional mechanical approach of decrypting-optimizing-reencrypting with a cryptographic approach where optimization operations are performed directly on encrypted data. This substitution eliminates the need to break encryption for optimization purposes, maintaining security while reducing operational complexity through direct ciphertext manipulation.
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.