Blockchain Search Engine for Mesh Network Content Caching
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Solution Overview
Problem
Conventional mesh networks face challenges in efficiently and cost-effectively managing and retrieving content due to increasing costs as the network expands, particularly in areas with limited Internet access, leading to suboptimal performance in posting, storing, and retrieving content.
Innovation Solution
Implementing a search engine based on a blockchain within the mesh network to determine frequently searched content, distribute it to cached nodes for quick retrieval, and utilize cryptocurrency for transactions, allowing for efficient content management and retrieval even in areas with limited Internet access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the mesh network expands dynamically to cover more areas, then the network coverage and accessibility are improved, but the cost associated with transactions and content retrieval increases
Solution Approach 1:
The system performs preliminary actions by identifying frequently searched content items before retrieval requests occur. The search engine analyzes search patterns and pre-positions this content on cached nodes within the mesh network, so that when retrieval requests occur, the content is already available locally, avoiding costly long-distance transmissions across the expanded network.
Solution Approach 2:
The system creates copies of frequently accessed content and distributes them to multiple cached nodes throughout the mesh network. Instead of retrieving the same content repeatedly from a single source across the expanded network, multiple local copies are made available, reducing transmission costs and improving retrieval efficiency as the network grows.
2Device complexity
If conventional mesh networks are used for content retrieval, then network simplicity is maintained, but the efficiency and speed of content retrieval deteriorates
Solution Approach 1:
The system introduces a search engine as an intermediary component that operates within the mesh network. This search engine analyzes search patterns, identifies frequently accessed content, and coordinates its distribution to cached nodes. The intermediary layer adds intelligence to the network without fundamentally changing the mesh structure, improving retrieval efficiency while maintaining network simplicity.
Solution Approach 2:
The system implements self-service mechanisms where the mesh network automatically identifies its own retrieval patterns and optimizes content distribution accordingly. The search engine monitors query frequencies and autonomously determines which content should be cached and where, allowing the network to self-optimize without external intervention or complex centralized control.
3Adaptability or versatility
If content is stored and retrieved from remote nodes in an expanded mesh network, then network versatility is improved, but the retrieval speed and access time increases
Solution Approach 1:
The system applies local quality by differentiating content storage locations based on access patterns. Frequently searched content is strategically positioned on cached nodes that are geographically or topologically closer to user devices, while less frequently accessed content remains on remote nodes. This creates a tiered storage architecture where the most important content is locally available, reducing retrieval time without sacrificing network versatility.
Data Source
AI summary
Systems as described herein may determine a plurality of content items posted to a mesh network and each content item may be associated with a signature stored in a blockchain. A search engine may query each content item based on the corresponding signature in the blockchain. The search engine may parse each content item to obtain a label and store the label, the signature and content associated with each content item in a database. The search engine may query the blockchain to obtain a frequency that each content item has been queried in a predetermined period of time. The search engine may rank the content items based on the frequencies, and determine a subset of the content items as frequently searched content. Accordingly, the search engine may distribute the frequently searched content to a plurality of cached nodes in the mesh network.