Video Home Office Cache Eviction via Traffic Prediction
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Solution Overview
Problem
Current video-on-demand systems face scalability issues due to the need for exact replication of content across all Video Home Offices (VHOs), leading to high storage costs and inefficiencies, as not all content is needed in every region and user behavior exhibits repetitive patterns.
Innovation Solution
Implementing a method where VHOs cache a subset of content from the Video Service Office (VSO) and use recorded traffic history metrics to predict future traffic, allowing them to fetch content from the VSO or other VHOs that minimizes network load and balances traffic across links, using algorithms to determine the best source for requested content based on predicted traffic costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If VHOs store exact replicas of all VSO content, then content access latency is reduced and reliability is improved, but storage costs and device complexity increase significantly
Solution Approach 1:
The patent segments the content library into different categories (popular content, less popular content, regional content) and distributes them across VSO and multiple VHOs. Each VHO stores only a subset of content rather than complete replicas, reducing storage requirements while maintaining content availability through intelligent routing and on-demand fetching.
Solution Approach 2:
The patent implements local quality by allowing different VHOs to store different subsets of content based on regional preferences and usage patterns. Each VHO optimizes its cache with locally relevant content while maintaining the ability to fetch content from other VHOs or the VSO, creating a heterogeneous caching strategy that reduces overall storage requirements.
2Speed
If VHOs store complete content replicas, then content delivery speed is improved, but network load during content updates increases
Solution Approach 1:
The patent applies partial action by having VHOs store only the most frequently accessed content locally rather than complete replicas. Less popular content is fetched on-demand from the VSO or other VHOs, reducing the network bandwidth required for content updates while maintaining fast delivery for popular content that is cached locally.
3Device complexity
If VHOs cache a subset of content, then storage costs are reduced, but content access time increases when content is not locally available
Solution Approach 1:
The patent implements preliminary action by pre-caching popular and frequently requested content at VHOs before user requests arrive. This allows the system to maintain reduced storage at VHOs while ensuring that high-demand content is already available locally, preventing access time penalties for popular content.
Solution Approach 2:
The patent introduces other VHOs as intermediaries in the content delivery chain. When a VHO needs content that is not in its local cache, it can fetch it from neighboring VHOs rather than directly from the VSO, reducing the access time penalty and distributing the fetch load across the network.
4Productivity
If VHOs use intelligent caching strategies, then storage efficiency is improved and network load is reduced, but system complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where VHOs monitor content access patterns, popularity metrics, and cache hit rates to dynamically adjust their caching strategies. This feedback-driven approach allows VHOs to automatically optimize which content to cache locally based on observed usage patterns, improving storage efficiency without requiring complex manual configuration.
Data Source
AI summary
A method and apparatus for downloading content within a video-on-demand system is provided herein. During operation a Video Home Office (VHO) will cache a subset of the Video Service Office (VSO) content. When a user requests content that is not stored on the VHO, the VHO will request that content from another VHO or the VSO. In order to reduce the additional network load imposed during item forwarding while attempting to balance the total load on all the links interconnecting the VSO and VHOs, recorded traffic history metrics are used to predict their future or current traffic. A VHO or VSO is chosen for fetching the content that will result in the lowest predicted traffic on the interconnecting links.