Tiered Distributed Architecture for Multimedia Search
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Solution Overview
Problem
Current multimedia content search and monitoring systems face challenges in scalability, real-time database searching, and handling large volumes of multimedia data with media content distortions, exceeding the capabilities of existing software solutions by an order of magnitude.
Innovation Solution
A distributed and tiered architecture for content search and monitoring that generates fingerprints for user-watched content, compares them with a reference database, and updates signatures in real-time using duplicate databases and circular buffers to optimize search efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large-scale multimedia database is searched in real-time, then content identification accuracy is improved, but search speed deteriorates
Solution Approach 1:
The patent segments the large multimedia database into multiple partitions or tiers, allowing the search system to divide and conquer the search space. This segmentation enables parallel processing of different database portions, maintaining search accuracy while improving overall search speed through distributed computation.
Solution Approach 2:
The patent implements preliminary indexing and preprocessing of multimedia content before actual search operations. By pre-computing and storing metadata, fingerprints, and structural information, the system prepares the database in advance to enable rapid real-time searching without compromising identification accuracy.
2Measurement precision
If the database is updated in real-time, then content monitoring accuracy is improved, but system complexity increases
Solution Approach 1:
The patent uses duplicate or copy databases that mirror the main database structure. When updates occur, the system can replicate changes to these copies, enabling real-time monitoring accuracy while distributing the complexity burden across multiple database instances rather than a single complex system.
Solution Approach 2:
The patent introduces intermediary components such as update buffers, synchronization mechanisms, and translation layers that mediate between data sources and the main database. These intermediaries simplify the update process by handling complexity in isolated modules, maintaining monitoring accuracy without proportionally increasing overall system complexity.
3Productivity
If distributed architecture is implemented, then scalability is improved, but communication overhead increases
Solution Approach 1:
The patent merges multiple distributed nodes into a coordinated system where computation and data are combined across the network. By strategically placing data and computation close to each other in the distributed architecture, the system achieves scalability while minimizing the communication distance and overhead between nodes.
Data Source
AI summary
An efficient large scale search system for video and multi-media content using a distributed database and search, and tiered search servers is described. Selected content is stored at the distributed local database and tier1 search server(s). Content matching frequent queries, and frequent unidentified queries are cached at various levels in the search system. Content is classified using feature descriptors and geographical aspects, at feature level and in time segments. Queries not identified at clients and tier1 search server(s) are queried against tier2 or lower search server(s). Search servers use classification and geographical partitioning to reduce search cost. Methods for content tracking and local content searching are executed on clients. The client performs local search, monitoring and/or tracking of the query content with the reference content and local search with a database of reference fingerprints. This shifts the content search workload from central servers to the distributed monitoring clients.