Demand-Based Content Caching Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for content distribution over the internet strains network resources, particularly during peak usage times, as traditional content caching methods are inefficient in managing diverse user requests and predicting content demand accurately.
Innovation Solution
The implementation of demand-based content caching systems that dynamically allocate cache resources at premises terminal devices based on content demand and prediction accuracy, allowing for more efficient use of network and cache resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional content caching methods are used, then content can be stored at network locations, but cache resource allocation is inefficient and cannot accurately predict diverse user content demands
Solution Approach 1:
The patent implements dynamic cache resource allocation where the content system continuously monitors cache access rates and modifies cache resource allocations in real-time based on actual content demand patterns. This dynamic adjustment mechanism enables accurate prediction of diverse user content demands while adapting cache allocation to changing conditions, resolving the contradiction between prediction accuracy and allocation complexity.
Solution Approach 2:
The system employs feedback loops where cache access rates are determined based on processed content requests and used to modify subsequent cache resource allocations. This feedback mechanism allows the system to learn from actual user behavior patterns and improve content demand prediction accuracy over time, while the automated feedback-driven allocation reduces manual complexity.
2Reliability
If more cache resources are allocated to content providers, then content availability improves, but network resource utilization during peak times deteriorates
Solution Approach 1:
The system performs preliminary actions by proactively pre-fetching and caching content that is predicted to be requested by users before actual demand occurs. By using cache access rates and content patterns to anticipate future requests, the system ensures content availability is already established in local caches before peak network usage times, eliminating the need for additional network resources during high-demand periods.
Solution Approach 2:
The patent implements self-service caching where individual premises terminal devices maintain and manage their own local content caches based on their specific user behavior patterns and content access rates. This distributed self-service approach ensures content availability at the edge without requiring centralized network resources, as each device independently serves its own content demands from local cache storage.
3Loss of time
If content is cached at premises terminal devices, then download times are reduced, but processing load shifts to user devices
Solution Approach 1:
The system applies partial action by caching only the most frequently accessed content portions at premises terminal devices based on cache access rate analysis. Rather than caching entire content libraries or over-provisioning cache resources, the system selectively caches specific content items that demonstrate high access rates, achieving significant download time reductions for critical content while minimizing the processing and storage burden on user devices.
Data Source
AI summary
Systems and methods for allocating cache resources on a premises terminal device based on cache allocation performance data are described. Cache resources on a premises terminal device are allocated to cache allocation entities (e.g., providers and/or user accounts) according to various parameters. A cache allocation factor may be determined based on the use of the associated cache resources over time, with allocations being reconfigured periodically based on the cache allocation factor. A cache allocation factor may be based on cache access hit rates, use of requested download windows, and the meeting of requested download deadlines.