Multi-Level Cache Hash Ring Tuning for SSD-HDD Response Efficiency
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Solution Overview
Problem
Current multilevel caches are prone to performance waste due to uncertainties in the performance ratio between different levels, such as a higher number of HDDs compared to SSDs, SSD failures, and varying performance over time, leading to inefficient use of resources and reduced response times.
Innovation Solution
A dynamic adjustment of request traffic based on the status of SSDs by periodically detecting IO queues and request latencies to generate a new hash ring, ensuring balanced distribution of requests across cache levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a multilevel cache system uses a fixed hash ring for request distribution, then the system structure is simple and easy to implement, but performance waste occurs due to uncertainties in the performance ratio between different cache levels
Solution Approach 1:
The patent implements dynamic adjustment of the hash ring based on real-time performance monitoring of different cache levels. The system continuously detects IO queue depths and request latencies, then dynamically reconfigures the hash ring to distribute requests according to current performance ratios, transforming the static cache system into an adaptive one that optimizes productivity without excessive complexity
Solution Approach 2:
The system establishes a feedback mechanism where performance metrics (IO queue depth, request latency) from each cache level are continuously monitored and fed back to the hash ring adjustment module. This feedback loop enables the system to automatically adjust request distribution based on actual performance ratios, resolving the contradiction between simple structure and high efficiency
2Quantity of substance
If more HDDs are used in the second-level cache to increase storage capacity, then storage capacity increases, but request response time increases due to slower access speed
Solution Approach 1:
The patent applies local quality by creating different request distribution strategies for different cache levels. The hash ring is configured to direct hot data requests to faster SSDs in the first-level cache, while cold data requests are routed to larger-capacity HDDs in the second-level cache. This localized optimization ensures that each cache level handles requests appropriate to its performance characteristics, minimizing overall response time while maintaining storage capacity
Solution Approach 2:
The system dynamically changes the parameter of request distribution ratios between cache levels based on data access patterns and performance metrics. By adjusting the hash ring configuration, the system can shift more requests to SSDs when performance is critical or utilize HDDs more extensively when storage capacity is the priority, thus balancing storage capacity and response time
3Speed
If SSDs are used in the first-level cache to improve access speed, then request response time decreases, but system cost increases due to higher storage device costs
Solution Approach 1:
The patent segments the cache system into two distinct levels with different performance characteristics and cost structures. The first-level cache using SSDs handles time-critical requests for hot data, while the second-level cache using HDDs handles less time-sensitive requests for cold data. This segmentation allows the system to achieve high-speed access where necessary while controlling costs by using cheaper storage for less critical operations
Solution Approach 2:
The system applies partial action by using SSDs only for the portion of data access that requires high speed (hot data in first-level cache), rather than using SSDs for all storage. The hash ring configuration ensures that only necessary requests are directed to expensive SSDs, while other requests are handled by more cost-effective HDDs, thus optimizing the balance between speed and cost
Data Source
AI summary
A multilevel-cache-based data processing method is provided, which is applied to a server computing device. The server computing device includes a first-level cache and a second-level cache. The first-level cache includes a plurality of first-type storage nodes. The second-level cache includes a plurality of second-type storage nodes. The data processing method includes identifying a target node based on a current hash ring in response to receiving a read request; determining whether the target node is any one of the plurality of first-type storage nodes; and in response to determining that the target node is not any one of the plurality of first-type storage nodes, reading response data from the plurality of second-type storage nodes for responding to the read request, and returning the response data. According to the method, a speed of responding to the read request can be increased, and pressure of the first-level cache can be reduced.