Metadata-Prioritized Image Cloning for WAN Bandwidth Optimization
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Solution Overview
Problem
Full cloning of computer images into a central location is challenging due to the complexity of managing multiple desktop images, geographic dispersion of large enterprises, and performance and scalability issues caused by variable bandwidths and latencies over Wide Area Networks, leading to inefficiencies in migration projects and user experience.
Innovation Solution
A mass centralization approach that uses metadata to prioritize and optimize the upload of files from multiple computing devices, determining the importance of files and distributing the upload workload based on disk read speed, network bandwidth, and user activity, allowing for rapid cloning of important assets while minimizing user interruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full cloning of computer images is performed using traditional file-system interfaces, then complete image backup is achieved, but the cloning process consumes excessive time and network resources
Solution Approach 1:
The patent applies preliminary action by performing metadata enumeration and file prioritization before the actual cloning process. The system pre-identifies important files based on metadata attributes (file type, size, modification time, location) and creates a prioritized upload list, so that when cloning begins, only critical files need to be transferred first, significantly reducing the time required to achieve functional backup readiness.
Solution Approach 2:
The patent implements partial action by cloning only the most important files first rather than waiting to clone entire image sets. By transferring a prioritized subset of files (metadata-enumerated important files) before complete image cloning, the system achieves sufficient backup functionality in less time, with less critical files cloned subsequently or on-demand.
2Reliability
If traditional disk cloning is used across multiple geographic locations over WAN links, then centralization is achieved, but network bandwidth and latency cause performance degradation
Solution Approach 1:
The patent applies local quality by adapting the cloning strategy to local network conditions at each computing device. The system enumerates metadata locally, determines file importance based on local priorities, and creates device-specific prioritized upload lists. This allows each location to optimize its upload sequence based on local file characteristics and network conditions, improving overall cloning efficiency across distributed WAN locations.
Solution Approach 2:
The patent implements partial action by transferring only the most critical files first over WAN links, rather than attempting to clone complete image sets across slow network connections. The prioritized file selection based on metadata attributes ensures that essential files are replicated centrally before less critical data, achieving functional centralization with reduced network resource consumption and improved productivity.
3Quantity of substance
If complete file content scanning is performed to identify duplicate files, then deduplication is achieved, but additional scanning time and CPU resources are consumed
Solution Approach 1:
The patent extracts and utilizes only the essential metadata attributes (file type, size, modification time, location) needed for prioritization, rather than performing complete file content scanning. By taking out and processing only these key metadata elements, the system achieves sufficient file identification and prioritization without the excessive time and CPU resources required for full content analysis, while still enabling effective cloning optimization.
4Reliability
If centralized cloning is applied to a large number of computing devices, then comprehensive backup is achieved, but scalability and performance challenges increase
Solution Approach 1:
The patent applies segmentation by dividing the centralized cloning task into independent per-device operations. Each computing device performs its own metadata enumeration, file prioritization, and upload sequence determination independently. This segmentation allows the system to scale to large numbers of devices without creating a centralized bottleneck, as each device autonomously manages its cloning process while contributing to the overall comprehensive backup goal.
Solution Approach 2:
The patent implements self-service by enabling each computing device to autonomously perform metadata enumeration, file prioritization, and upload scheduling without requiring centralized coordination for each device. The devices independently determine their own optimal upload sequences based on their local file systems and network conditions, reducing system complexity and improving scalability while still achieving comprehensive centralized backup.
Data Source
AI summary
A system for a mass centralization approach to full image cloning of multiple computing devices is provided. The system includes a plurality of computing devices and a server. The server includes a processor programmed to receive, from the plurality of computing devices, metadata for files stored on the plurality of computing devices, determine, from the received metadata, an importance level for each of the files, instruct the plurality of computing devices to send a copy of the files to the server in a defined order, the defined order based on the importance level for each of the files, and store the copy of the files on the server.