Edge-Fog-Cloud Content Provisioning for AR Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing content provisioning systems for augmented reality lack efficient methods to provide location-specific content to users in real-time, especially in dynamic environments where latency and computational resources are a concern.
Innovation Solution
A content provisioning system that utilizes a mobile device with a head-worn viewing component, connected to edge, fog, and cloud resource devices via wireless connections. This system employs a spatial computing layer to integrate data resources, determine geographic parameters, and provide location-specific content to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If content provisioning is done using traditional centralized systems, then system simplicity is maintained, but latency increases and real-time performance deteriorates
Solution Approach 1:
The patent segments the content provisioning system into multiple distributed components: edge servers located near content sources, fog nodes positioned in intermediate networks, and cloud infrastructure. This segmentation enables parallel content delivery through multiple paths, reducing latency while distributing system complexity across independent modules rather than concentrating it in a single centralized system.
Solution Approach 2:
The patent introduces a multi-dimensional content provisioning architecture that adds spatial and hierarchical dimensions to the traditional flat centralized model. By creating edge-fog-cloud layers at different network distances and computational levels, the system delivers content through optimized paths selected based on multiple dimensions including geographic proximity, network conditions, and content type, thereby reducing latency without oversimplifying system design.
2Speed
If computational tasks are centralized in cloud resources, then device complexity is reduced, but processing speed and real-time response deteriorate
Solution Approach 1:
The patent applies local quality by positioning computational resources at different network locations with different capabilities. Edge servers provide low-latency processing for time-sensitive tasks near content sources, fog nodes handle intermediate processing for moderate complexity tasks, and cloud infrastructure manages high-complexity batch processing. This local differentiation optimizes processing speed for each task type while distributing computational architecture complexity across specialized nodes.
Solution Approach 2:
The patent implements dynamic task offloading that adapts computational architecture based on real-time conditions. The system dynamically selects which nodes (edge, fog, or cloud) should process specific tasks based on current network conditions, task complexity, and resource availability. This dynamic approach enables fast processing when edge resources are available while allowing flexible redistribution of computational complexity to fog or cloud when needed, optimizing both speed and architectural efficiency.
3Measurement precision
If location-specific content is provided using centralized provisioning, then system management is simplified, but content delivery accuracy and relevance deteriorate
Solution Approach 1:
The patent implements preliminary localization at edge servers that are geographically positioned near content sources and target users. Edge servers perform initial location determination using local sensors and environmental data before content provisioning occurs. This preliminary action at the network edge enables accurate location-based content selection without requiring complex centralized processing, as location context is captured and processed locally before being passed to higher-level system components.
Solution Approach 2:
The patent introduces fog nodes as intermediaries between edge sensors and cloud content management systems. These fog nodes aggregate and refine location data from multiple edge sources, applying local context understanding to enhance location accuracy. The intermediary fog layer translates raw sensor data into refined location context that improves content relevance while distributing the computational burden of location processing across the edge-fog-cloud hierarchy, reducing the complexity burden on any single component.
4Reliability
If multiple resource devices are distributed across edge, fog, and cloud, then content provisioning robustness is improved, but system complexity increases
Solution Approach 1:
The patent designs edge, fog, and cloud nodes with universal interfaces and standardized protocols that enable them to perform multiple functions depending on their operational context. Each node type can handle content caching, processing, and delivery tasks, allowing the system to dynamically allocate functions across the distributed architecture based on conditions rather than requiring specialized dedicated components. This multi-functionality improves robustness through flexible resource allocation while reducing the complexity of managing truly specialized heterogeneous systems.
Solution Approach 2:
The patent implements feedback mechanisms where distributed edge, fog, and cloud nodes continuously exchange status information about content availability, processing capacity, and network conditions. This feedback enables automatic load balancing and failover: when one node experiences issues, the system receives feedback and dynamically redirects tasks to alternative nodes. The feedback-driven coordination improves provisioning robustness while using standardized feedback protocols to manage distributed complexity systematically rather than requiring complex manual coordination of each node.
Data Source
AI summary
The invention provides a content provisioning system. A mobile device has a mobile device processor. The mobile device mobile device has communication interface connected to the mobile device processor and a first resource device communication interface and under the control of the mobile device processor to receive first content transmitted by the first resource device transmitter The mobile device mobile device has a mobile device output device connected to the mobile device processor and under control of the mobile device processor capable of providing an output that can be sensed by a user.