Edge Node Content Agent Registry for Mesh Network Delivery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current content delivery systems in mesh networks face challenges in managing and delivering content efficiently to edge nodes, particularly in detecting new content in central storage and ensuring the appropriate application is running for the content, leading to potential delays and inefficiencies.
Innovation Solution
A content agent registry is implemented to identify and manage content based on attributes, allowing for the automatic delivery of content and associated applications to edge nodes, enabling predictive, scheduled, and location-specific content distribution, and ensuring the most appropriate application is used.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content is stored centrally in cloud storage, then control and management of content is improved, but communication links to network edge must be good to retrieve content efficiently
Solution Approach 1:
The patent implements a distributed content storage architecture where content is replicated across multiple edge nodes in the mesh network. Each edge node maintains a local copy of content, allowing users to access content from the nearest edge node rather than retrieving from central cloud storage. This resolves the contradiction by maintaining centralized management control while enabling fast local retrieval through distributed replication.
Solution Approach 2:
The content agent registry proactively pushes content updates to edge nodes before users request them. When new content is added to the cloud, the content agent automatically identifies affected edge nodes and pushes the content in advance. This preliminary action ensures content is already available at the network edge when needed, eliminating retrieval delays while maintaining centralized control over what content is distributed.
2Measurement precision
If manual checks are performed to detect new content in central storage, then content delivery accuracy is improved, but time consumption and inefficiency increase
Solution Approach 1:
The content agent registry implements a push-based feedback mechanism where the central cloud storage system automatically notifies edge nodes when new content is added. The content agent monitors the cloud storage for content changes and immediately pushes updates to relevant edge nodes without waiting for manual checks. This feedback loop maintains high detection accuracy while eliminating the time loss associated with manual content verification.
Solution Approach 2:
The system enables self-service content update detection where the content agent registry autonomously monitors cloud storage for new content and automatically pushes updates to edge nodes. No manual intervention is required - the system self-manages the detection and distribution of new content, achieving both high accuracy in detecting updates and eliminating the time consumption of manual checks.
3Productivity
If content is pushed to edge nodes based on characteristics, then content delivery efficiency is improved, but complexity of managing content attributes increases
Solution Approach 1:
The content agent registry serves multiple functions within a single system: it maintains the registry of content characteristics, identifies which edge nodes should receive which content, manages the pushing of content updates, and tracks content delivery status. By consolidating these multiple functions into a universal content agent registry, the system achieves efficient characteristic-based content delivery without proportionally increasing management complexity.
Solution Approach 2:
The system manages content characteristics as standardized parameters (such as content type, target audience, delivery timing) that can be efficiently queried and matched. By defining a structured set of content parameters in the registry, the system enables automated matching of content to edge nodes based on these parameters, improving delivery efficiency while keeping the complexity of parameter management tractable through standardization.
Data Source
AI summary
A network entity is provisioned to support cloud services for a mesh network that includes at least one edge node. The network entity comprises: a processor, operably coupleable to a content store; and a content agent registry coupled to the processor and configured to identify content to be delivered to the at least one edge node. The content agent registry records at least one attribute against the content to be delivered based on a characteristic of the content.