Edge Computing System for Real-Time User Data Processing
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Solution Overview
Problem
Conventional computing systems face delays in providing personalized content to users due to inefficient data processing and transmission, especially in cloud-based models, which results in inaccurate content identification and lost targeting opportunities, exacerbated by the rise in internet-connected devices straining available bandwidth.
Innovation Solution
Implementing a system that processes user data on edge devices using edge computing, distributing processing tasks away from centralized servers, and storing only necessary data locally, allowing for real-time user segmentation and content delivery without relying on continuous cloud data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based batch processing is used to analyze user data, then content personalization can be achieved, but processing time delays content delivery by 12-24 hours
Solution Approach 1:
The patent segments the centralized cloud processing into distributed edge processing units deployed across multiple devices. Each edge device independently processes user data locally, eliminating the need for centralized batch processing and enabling real-time content personalization without 12-24 hour delays.
Solution Approach 2:
The patent transitions from a single centralized processing dimension (cloud servers) to multiple distributed processing dimensions (edge devices throughout the network). This dimensional shift enables parallel processing of user data across numerous devices simultaneously, reducing overall processing time while maintaining personalization accuracy.
2Measurement precision
If vast amounts of user data are transmitted to cloud servers for processing, then accurate user profiling can be created, but bandwidth constraints slow down data transmission
Solution Approach 1:
The patent extracts the data processing function from centralized cloud servers and places it at the edge devices where user data is generated. This extraction eliminates the need to transmit vast amounts of user data across the network, as processing occurs locally at the source, thereby resolving bandwidth constraints while maintaining profiling accuracy.
Solution Approach 2:
Edge devices perform self-service by independently processing user data locally without requiring continuous communication with centralized servers. Each edge device autonomously creates and updates user profiles using local computational resources, eliminating bandwidth-dependent data transmission while preserving profiling precision.
3Productivity
If user data is processed and stored in centralized cloud servers, then comprehensive analysis can be performed, but security risks increase with centralized data storage
Solution Approach 1:
The patent segments centralized data storage and processing into distributed storage and processing across multiple edge devices. User data remains localized at edge devices rather than being集中 stored in centralized servers, maintaining comprehensive analysis capability through distributed computation while reducing security risks associated with centralized data repositories.
4Measurement precision
If new user segments are created by processing vast amounts of user data in the cloud, then accurate targeting can be achieved, but the process creates a bottleneck that delays segment implementation
Solution Approach 1:
Edge devices perform self-service by independently creating and updating user segments locally using distributed processing. Each edge device autonomously analyzes user data and creates targeted segments without requiring centralized cloud processing, eliminating the bottleneck that delays segment implementation while maintaining targeting accuracy through local computational capabilities.
Data Source
AI summary
A method for displaying content to a user at a user device, the method comprising: initiating, at the user device, a web element request indicative of a web element; transmitting, at a web element server, the web element to the user device in response to the web element request; receiving, at a code provisioning server, a code portion request in response to the web element request; transmitting, at the code provisioning server, a code portion to the user device in response to the code portion request; executing, at the user device, the code portion in response to the web element request, wherein executing the code portion causes a processor at the user device to: collate user data at the user device; and generate an instruction to execute an action based on the collated user data.