QOS-Driven Dynamic Cache Update System for Client Request Prioritization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional cache update methods apply a single static mechanism for all client requests, ignoring client urgency and quality of service (QOS) levels, which can lead to suboptimal user experiences in data storage configuration and management operations.
Innovation Solution
A quality of service (QOS)-driven dynamic cache update system that determines the QOS level based on prior client requests, allowing for varying cache update processing to prioritize user experience, with three predefined QOS levels (QOS=1, QOS=2, and QOS=3) to manage when updates are applied to cached data storage configuration information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single static cache update mechanism is applied to all client requests, then the system is simple to implement, but user experience deteriorates due to inability to prioritize urgent requests
Solution Approach 1:
The patent implements dynamic cache update mechanisms that adapt to different client request characteristics. The system transitions from a static single-mode update approach to multiple dynamic update modes (synchronous, asynchronous, deferred) selected based on QOS levels and client behavior patterns, thereby improving user experience while managing complexity through contextual adaptation
Solution Approach 2:
The patent applies different cache update strategies to different client requests based on their specific QOS levels and behavior patterns. High-QOS clients receive synchronous updates with immediate cache refreshes, while low-QOS clients receive deferred updates, allowing localized optimization of cache update quality for different client segments without uniformly increasing system complexity
2Reliability
If cache updates are applied immediately for all requests, then cache freshness is improved, but system response time deteriorates due to unnecessary processing overhead
Solution Approach 1:
The patent changes the timing parameter of cache updates based on QOS levels and client behavior patterns. For high-QOS clients with urgent needs, cache updates are performed synchronously with immediate application. For low-QOS clients, cache updates are deferred to asynchronous processing or batch operations, optimizing the balance between cache freshness and response time through parameter-based differentiation
Solution Approach 2:
The patent implements periodic and batched cache update mechanisms for low-QOS clients, where updates are applied at predetermined time intervals or when a threshold of changes is reached, rather than immediately with each client request. This reduces system response time while maintaining acceptable cache freshness through periodic synchronization
3Reliability
If synchronous cache updates are performed for all clients, then data consistency is improved, but system productivity deteriorates due to blocking client responses
Solution Approach 1:
The patent dynamically selects between synchronous and asynchronous cache update modes based on client QOS levels. High-QOS clients receive synchronous updates that block until cache consistency is ensured, while low-QOS clients receive asynchronous updates that return immediately, allowing the system to maintain data consistency for critical clients while preserving overall system throughput and productivity
Solution Approach 2:
The patent segments the client base into different QOS groups and applies different cache update strategies to each segment. This segmentation allows critical high-QOS clients to receive guaranteed consistent updates while low-QOS clients receive best-effort updates, thereby maintaining data consistency for important operations without blocking system-wide productivity
4Productivity
If cache updates are deferred for low-QOS clients, then system productivity is improved, but cache freshness deteriorates
Solution Approach 1:
The patent implements periodic cache refresh mechanisms for deferred update scenarios. Even though low-QOS clients receive asynchronous or deferred updates, the system periodically re-synchronizes the cache with the underlying data storage to ensure that cache freshness is maintained within acceptable bounds, balancing productivity gains with reliability requirements
Solution Approach 2:
The patent employs feedback mechanisms where the system monitors cache staleness and client access patterns. When cache data becomes too stale or when a low-QOS client accesses data that has been updated, the system triggers additional cache refresh operations, ensuring that cache freshness is maintained through adaptive feedback-driven updates
Data Source
AI summary
Described are techniques for processing requests. A profile is recorded comprising a plurality of prior requests from a client to a server. The plurality of prior requests associated with first data. A cached copy of the first data is stored in a cache of the server. A quality of service associated with the received request is determined for affecting when the update is applied to the cached copy of first data. The quality of service associated with the received request is dependent on the prior requests in the profile. The first update is applied to the first data. In accordance with the quality of service, the first update is applied to the cached copy of the first data.