Cache Quota Allocation via Hit-Based Simulation
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Solution Overview
Problem
Cache memory efficiency is hindered by uneven distribution of hits over time for different storage entities, leading to suboptimal allocation of cache resources, as existing methods fail to account for changing hit patterns and write rates, resulting in reduced overall cache performance.
Innovation Solution
A method that dynamically allocates cache space by dividing it into virtual slices based on expected hit scores, iteratively assigning quotas to storage entities that maximize hits, considering the distribution of hits over time and write rates, ensuring that each entity receives the optimal number of quotas to maintain high cache performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cache space is allocated using traditional methods, then allocation is simple, but cache efficiency deteriorates due to uneven hit distribution
Solution Approach 1:
The patent implements dynamic quota allocation that adapts to changing hit patterns over time. The system continuously monitors hit distributions and adjusts cache quotas accordingly, transitioning from static to dynamic allocation to maintain optimal cache efficiency as workloads evolve.
Solution Approach 2:
The system changes the allocation parameters from equal or fixed quotas to variable quotas based on observed hit patterns. By analyzing hit distributions and adjusting quota parameters dynamically, the system optimizes cache performance without requiring complete redesign of the allocation mechanism.
2Productivity
If cache quotas are allocated equally to all storage entities, then allocation is fair and simple, but overall cache performance deteriorates due to ignoring different hit patterns
Solution Approach 1:
The patent applies different quota allocations to different storage entities based on their specific hit patterns. Instead of uniform treatment, each entity receives customized quota proportions matched to its access characteristics, allowing optimal performance for each while maximizing total cache hits.
Solution Approach 2:
The system dynamically adapts quota allocations to match changing hit patterns of different storage entities. As workloads evolve and hit distributions change, the allocation system adjusts accordingly, maintaining adaptability to diverse and time-varying access patterns.
3Productivity
If cache space is reallocated frequently to optimize hits, then cache efficiency improves, but system complexity and overhead increase
Solution Approach 1:
The system implements periodic monitoring and evaluation of hit patterns rather than continuous reallocation. By establishing evaluation cycles and thresholds, the system determines when rebalancing is necessary, reducing overhead while maintaining cache efficiency through scheduled optimization.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor cache hit patterns and trigger reallocation only when performance degradation is detected. This feedback-driven approach optimizes the timing of rebalancing operations, improving cache hit rates while minimizing unnecessary reallocation overhead.
Data Source
AI summary
A method, storage system and non-transitory computer readable medium. The method may include receiving or generating, and for each storage entity out of multiple storage entities of the storage system, a storage entity distribution of cache hits over a caching period related to cached data associated with the storage entity and determining an allocation of quotas of the cache space to the multiple storage entities. The determining may include: (a) for each storage entity, determining a hit score indicative of a number of cache hits per a caching sub-period of the caching period related to the storage entity; (b) simulating, in an iterative manner, an allocation of quotas of the cache space to the storage entities that substantially maximizes the number of cache hits; and (c) allocating quotas of the cache space to the storage entities of the multiple storage entities, based on an outcome of the simulation.