Edge Computing Metadata Prediction for 5G Latency

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Solution Overview

Problem

Current systems for distributing content in 5G networks face high latency and costs due to the aggregation of personalized and non-personalized metadata, which requires additional cloud resources and traffic for each user request, especially when user devices exhibit repetitive usage patterns.

Innovation Solution

Implementing a method where edge computing systems in 5G networks predict user device activity patterns and cache relevant metadata, reducing the need for frequent requests to the cloud system by pre-fetching and storing information based on determined likelihoods and expected utility, thereby optimizing resource usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If metadata aggregation is performed in the cloud system for each user request, then personalized metadata can be provided, but latency and cloud resource costs increase

Engineering Contradiction:

Improvepersonalized metadata accuracyVSAvoidresponse latency

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by predicting user device activity patterns and pre-fetching metadata from the cloud system before actual requests occur. The edge computing system stores this predicted metadata in advance, so when a user device connects and requests content, the metadata is already available locally, eliminating the need for real-time cloud processing and significantly reducing latency.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If cloud system processes each user request individually, then accurate personalized responses are generated, but cloud traffic and resource utilization increase

Engineering Contradiction:

Improvemetadata accuracyVSAvoidcloud traffic

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The edge computing system acts as an intermediary between user devices and the cloud system. It receives and processes requests locally, generating metadata using stored activity pattern information. Only when the edge system needs additional data does it communicate with the cloud, significantly reducing cloud traffic while maintaining metadata accuracy through the edge system's local processing capabilities.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Speed

If edge computing systems cache more user information, then request response speed improves, but edge system storage requirements increase

Engineering Contradiction:

Improvecontent delivery speedVSAvoidedge storage capacity

Core Design Contradiction:

SpeedVSVolume of stationary object

Solution Approach 1:

Instead of caching all possible user information, the system uses partial action by caching only the metadata and activity patterns that are most likely to be needed based on predictions. The edge computing system stores selected user activity patterns and metadata that will be useful for upcoming requests, balancing storage usage with response speed improvements.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11184453B2Systems and methods for managing content in a network

Publication Date: 2021.11.23 SYNAMEDIA LTD

AI summary

A method for managing content in a network having one or more user devices and one or more edge computing systems includes determining a likelihood that a user device will connect to an edge computing system during a time window, based on the determined likelihood, storing on the edge computing system information reflecting an activity pattern associated with the user device, receiving a request for content from the user device, generating metadata based on the stored information and the request, and transmitting the metadata to the user device.