Virtual Machine Introspection Semantic Reconstruction
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Solution Overview
Problem
Virtual Machine Introspection (VMI) technologies face the challenge of the semantic gap, where they can only monitor VMs at a low-level, bit-wise data level, lacking higher-level abstraction and semantic information, which limits their ability to effectively analyze and optimize VM operations.
Innovation Solution
A method and device that reconstruct semantic information by parsing metadata using symbol table information and source code of the VM's operating system, allowing the Hypervisor to access and modify memory areas and schedule virtual machine programs based on high-level semantic information, without modifying the VM's operating system or adding new modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If VMI technology monitors VM at Hypervisor level to obtain complete view of hardware resources, then monitoring capability is improved, but data remains at low-level bit/byte format lacking semantic information
Solution Approach 1:
The patent introduces an intermediary component that translates low-level bit/byte data from the Hypervisor into high-level semantic information. This intermediary layer parses raw monitoring data and reconstructs meaningful operational semantics, thereby resolving the information loss while preserving the complete monitoring view capability.
Solution Approach 2:
The patent transforms the parameter representation of monitoring data from low-level binary formats to high-level semantic parameters. By changing the data representation parameters and introducing abstraction layers, the system recovers semantic information without sacrificing the underlying monitoring precision.
2Productivity
If Hypervisor accesses and analyzes VM memory data to reconstruct semantic information, then operational analysis capability is improved, but system complexity and processing burden increase
Solution Approach 1:
The patent segments the semantic information reconstruction process into modular components that operate independently. By dividing the complex analysis task into discrete functional units, the system improves operational analysis capability while managing complexity through modular architecture.
Solution Approach 2:
The patent performs preliminary processing and organization of VM memory data before full semantic reconstruction. By pre-processing data in stages and preparing it systematically, the system enhances analysis capability while reducing the immediate processing burden on the Hypervisor.
Data Source
AI summary
A method for implementing a virtual machine introspection includes: receiving a read request to access a memory area of a virtual machine through a Hypervisor for data reading; the Hypervisor accessing the memory area of the virtual machine to perform an operation of reading data according to the read request to return an operation result; and reconstructing semantic information based on the operation result, on an apparatus located outside a virtualization system that includes the Hypervisor.