Virtual Machine Image Upload Error Detection
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Solution Overview
Problem
In cloud computing environments, retrieving and uploading virtual machine images from a client device to a network-accessible computing platform is resource-intensive and bandwidth-consuming, as the platform often creates new images from scratch, and existing images on the client device are not efficiently utilized, leading to unnecessary resource usage and error detection processes.
Innovation Solution
A method where the client device transmits virtual machine images in a compressed stream to the cloud platform, simultaneously reconstituting and performing error detection on a second stream, allowing for early error detection and halting of uploads, thus freeing resources on both the client and cloud sides.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual machine images are retrieved and uploaded from client device to cloud platform, then the platform can utilize existing images, but resource utilization and bandwidth consumption increase significantly
Solution Approach 1:
The patent performs error detection and validation of virtual machine images at the client device before uploading to the cloud platform. This preliminary action includes checking image integrity, verifying compatibility, and detecting errors locally, so that only valid images are transmitted. This prevents waste of bandwidth and cloud resources on uploading corrupted or incompatible images.
Solution Approach 2:
The patent extracts the error detection and validation functions from the cloud platform and relocates them to the client device. By taking out these validation tasks and performing them locally, the system avoids uploading invalid images that would consume cloud resources, thereby reducing overall resource utilization and bandwidth consumption.
2Reliability
If error detection is performed after complete upload of VM images, then comprehensive validation is achieved, but resource waste occurs during upload of potentially invalid images
Solution Approach 1:
The patent performs comprehensive error detection and validation at the client device before initiating the upload process. This preliminary validation includes checking image integrity, verifying format compatibility, and detecting corruption. By completing these checks beforehand, the system ensures that only valid images are uploaded, preventing waste of bandwidth and cloud resources while maintaining reliable error detection.
Solution Approach 2:
The patent enables the client device to perform self-validation of virtual machine images using local computational resources. The client device independently checks image integrity, verifies compatibility requirements, and detects errors without requiring cloud platform intervention during the validation phase. This self-service approach filters out invalid images before upload, reducing resource waste.
3Measurement precision
If VM images are uploaded in uncompressed format, then error detection is more accurate, but bandwidth consumption and upload time increase
Solution Approach 1:
The patent performs error detection on compressed virtual machine image data at the client device before upload. By conducting validation checks on the compressed format itself, the system maintains error detection accuracy without requiring decompression. This approach verifies image integrity and compatibility while keeping the data in its compact compressed state, thereby minimizing bandwidth consumption and upload time.
Data Source
AI summary
Architectures and techniques for uploading virtual machine (VM) images to a network-accessible computing platform from a client device while simultaneously performing error detection of the VM images at the client device. One technique can include transmitting a request from the client device to upload VM images. The technique can further include receiving an application from the computing platform and using the application to reconstitute the VM images from a first stream at the client device while performing error detection. The technique also includes using the application to upload the VM images from a second stream at the client device to the computing platform while performing the error detection.