Edge-Node Resource Distribution for Retail Traffic
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Solution Overview
Problem
Existing methods for resource allocation across different access channels, such as online stores, mobile applications, and brick-and-mortar locations, often result in inefficient use and waste of resources due to unpredictable customer demand, leading to suboptimal customer satisfaction and increased costs.
Innovation Solution
Implementing edge-node controlled computing resource distribution, where sensors and actuators in an IoT network detect and respond to real-time customer traffic and resource usage, dynamically reallocating resources and redirecting customers to locations with available resources, using edge-nodes for data processing and decision-making close to the source of data to reduce latency and improve efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are allocated based on peak demand to ensure customer satisfaction, then service quality is improved, but resource waste increases due to over-supply during low-demand periods
Solution Approach 1:
The patent implements dynamic resource allocation where computing resources are not statically assigned but dynamically adjusted based on real-time customer demand. Edge nodes continuously monitor traffic patterns and automatically scale resource allocation up or down, allowing the system to maintain high service quality during peak demand while minimizing resource waste during low-demand periods.
Solution Approach 2:
The system incorporates feedback mechanisms where edge nodes continuously monitor customer traffic, resource utilization metrics, and service quality indicators. This feedback loop enables the system to detect demand changes in real-time and automatically adjust resource allocation, ensuring that resources are optimized based on actual conditions rather than static predictions.
2Adaptability or versatility
If resources are distributed across multiple access channels to improve service coverage, then customer accessibility is improved, but resource utilization efficiency decreases due to unpredictable demand patterns
Solution Approach 1:
The patent segments the resource allocation system into multiple independent edge nodes, each responsible for a specific access channel or geographic region. This segmentation allows each edge node to independently optimize resource allocation for its local conditions while maintaining overall system-wide efficiency through coordinated operation.
Solution Approach 2:
The edge nodes are designed with multi-functionality, capable of serving multiple access channels (online store, mobile application, brick-and-mortar locations) simultaneously. Each edge node can dynamically allocate resources across different channels based on real-time demand, making the system universally adaptable while maintaining efficient resource utilization.
3Reliability
If threshold levels of resources are maintained in all locations to ensure availability, then service reliability is improved, but operational costs increase due to redundant resource distribution
Solution Approach 1:
The patent introduces edge nodes as intermediary components between central resource pools and end-user access channels. These edge nodes act as smart intermediaries that cache and manage resources locally based on predicted and actual demand, reducing the need to maintain high threshold levels at all locations while ensuring service availability through intelligent resource distribution.
Data Source
AI summary
This application describes apparatus and methods for using edge-computing to control resource distribution among access channels, such as a retail banking center. Edge-nodes may be configured to move a product display in response to detected or expected customer traffic flow in or near a retail location. Edge-nodes may be configured to redirect resources provided by a cloud computing environment to or away from the retail location. Based on customer traffic flow, edge-nodes may direct customers/resources to a retail location and ensure the retail location provides a predetermined quality of service.