ICN Distributed Search with Approximate Cache and Semantic Prefix
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Solution Overview
Problem
Traditional Information Centric Network (ICN) frameworks lack efficient semantic matching techniques, leading to high computational and storage demands, and require globally synchronized models for fuzzy interest forwarding, which is not scalable.
Innovation Solution
An efficient mechanism is introduced that uses a naming scheme with a prefix for approximate search, a similarity score threshold, and a maximum number of data entries to retrieve, along with inverted indices for the content store and forwarding information base, allowing for proactive maintenance and faster information location and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ICN frameworks use exact matching of interest names with data names, then routing precision is maintained, but semantic matching efficiency deteriorates and computational demands increase
Solution Approach 1:
The patent segments the interest name into multiple components including a semantic prefix and specific content identifier. The semantic prefix is used for approximate matching to improve efficiency, while the specific content identifier maintains routing precision. This segmentation allows the system to perform fast prefix-based semantic matching while preserving exact matching capability for precise routing.
Solution Approach 2:
The patent applies different matching strategies to different parts of the interest name. The semantic prefix portion uses approximate matching with similarity scoring for efficient semantic search, while the content identifier portion uses exact matching for precise routing. This local differentiation of matching quality resolves the contradiction between semantic efficiency and routing precision.
2Productivity
If ICN frameworks implement semantic matching techniques, then information retrieval efficiency improves, but computational and storage demands increase
Solution Approach 1:
The patent implements partial semantic matching by using only the semantic prefix portion of interest names for approximate matching, rather than analyzing entire content. This partial action approach provides sufficient semantic matching efficiency while significantly reducing computational and storage resource requirements compared to full-content semantic analysis.
Solution Approach 2:
The patent uses lightweight inverted indices built from semantic prefixes rather than comprehensive semantic representations. These simplified index structures require minimal storage resources and can be constructed and updated efficiently, providing semantic matching capability with low computational overhead.
3Stability of the object's composition
If ICN frameworks use globally synchronized models for fuzzy interest forwarding, then matching consistency improves, but scalability deteriorates
Solution Approach 1:
The patent segments the semantic matching function into distributed inverted indices maintained at individual network nodes rather than a centralized global model. Each node independently maintains its own inverted index for the semantic prefixes of content it stores, enabling scalable distributed semantic matching while maintaining consistency through the standardized prefix-based approach.
Solution Approach 2:
Each network node autonomously maintains its own inverted index for semantic prefix matching without requiring global synchronization. Nodes independently perform semantic matching using their local indices, enabling the system to scale distributedly while maintaining matching consistency through the standardized prefix-based semantic representation.
4Loss of information
If ICN frameworks perform comprehensive content search, then search completeness improves, but search speed deteriorates
Solution Approach 1:
The patent segments the search process into two stages: first, fast filtering using inverted indices on semantic prefixes to identify candidate content, and second, more detailed matching on the filtered results. This segmentation enables the system to maintain search completeness while dramatically improving search speed by avoiding comprehensive search of all content.
Solution Approach 2:
The patent performs partial semantic matching using only the semantic prefix portion of content names rather than analyzing complete content. This partial action provides sufficient search capability for most semantic queries while significantly reducing search time and computational resources required for comprehensive content analysis.
Data Source
AI summary
Systems and techniques for an information centric network (ICN) distributed search with approximate cache and forwarding information lookup. For example, a search interest packet may be received. Here, the search interest packet includes search criteria and a signal indicating that it is a search interest packet. A search for content—including content in a local content store—that meets the search criteria may then be performed. Once complete, a data packet that includes the results of the search may be transmitted towards an author of the search interest packet.