Adaptive Virtual I/O Channels for Latency Reduction
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Solution Overview
Problem
Virtualization of computer systems leads to I/O over-subscription, resulting in degraded throughput performance and increased latency due to the shared I/O access architecture, which conventional methods inadequately address.
Innovation Solution
The implementation of adaptive virtual I/O channels with entropy detection and queue storage modules that encode I/O request data, manage I/O queues based on entropy values, and optimize memory utilization through compression, thereby improving I/O resource allocation and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple virtual machines share physical I/O resources through virtualization, then resource utilization efficiency is improved, but I/O throughput performance degrades due to over-subscription
Solution Approach 1:
The patent segments I/O resources by creating separate I/O queues for different virtual machines and I/O operations. The I/O manager divides the shared physical I/O resources into multiple virtual I/O channels, each with its own queue, allowing independent management and prioritization of I/O requests from different VMs, thus preventing one VM from monopolizing I/O bandwidth
Solution Approach 2:
The patent dynamically changes I/O processing parameters including queue priorities, buffer sizes, and scheduling policies based on system conditions and VM requirements. The I/O manager adjusts these parameters in real-time to optimize throughput while maintaining fair resource distribution among multiple virtual machines
2Device complexity
If I/O requests are processed through a shared I/O access architecture, then system complexity is reduced, but latency increases due to processing path length
Solution Approach 1:
The patent implements preliminary actions by pre-allocating I/O queues and buffers for each virtual machine before I/O requests arrive. The I/O manager prepares multiple ready-to-use queue structures and memory buffers in advance, so that when I/O requests come from different VMs, they can be immediately routed to pre-configured queues without dynamic allocation overhead, reducing processing latency
Solution Approach 2:
The patent introduces an I/O manager as an intermediary layer between the virtual machines and physical I/O devices. This intermediary consolidates I/O requests from multiple VMs, performs batch processing where applicable, and manages queue prioritization, thereby reducing the overall processing path length and latency while maintaining the simplicity of the shared architecture
3Speed
If I/O queues are managed without compression, then processing speed is maintained, but memory utilization efficiency decreases
Solution Approach 1:
The patent applies partial compression selectively to I/O queue data based on compression ratio thresholds and data characteristics. The I/O manager compresses only those queue entries or buffer data that meet specific criteria (e.g., high redundancy, large size), leaving time-critical or already-compressed data uncompressed, thus achieving memory efficiency improvement without significant impact on processing speed
Solution Approach 2:
The patent dynamically changes compression parameters including compression level, algorithm selection, and trigger thresholds based on queue depth, data type, and system load. The I/O manager adjusts these parameters in real-time to optimize the balance between memory utilization and processing speed, applying higher compression when memory is constrained and lower compression when throughput is critical
Data Source
AI summary
A system and method for processing input/output (I/O) requests in a virtualized computer system. I/O requests are received from a virtual machine. A set of virtual I/O channels that may be interfaced with a host I/O stack and/or a virtual machine I/O stack adaptively queues requested data using a variety of I/O queue management modules. In one embodiment, the virtual I/O channels include an entropy detection module and a queue storage. The entropy detection module determines an entropy value of specified I/O request data and encodes the specified I/O request data with the entropy value within the queue storage.