Edge Enabling Layer Analytics for Proactive EAS Continuity

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Solution Overview

Problem

The existing Edge Enabler Layer (EEL) lacks support for proactive EAS instantiation and predictive selection of common EAS based on analytics information, leading to potential service interruptions and delays in scenarios like real-time communication and multi-user sessions.

Innovation Solution

Integrate an analytics service (ADAES) to provide predictive analytics for service continuity, enabling proactive detection of ACR triggers, recommendation of T-EES and/or T-EAS, and proactive EAS instantiation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If EAS instantiation is performed reactively after service request, then service resource availability is improved, but service delay and interruption occur

Engineering Contradiction:

Improveservice continuityVSAvoidservice delay

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The analytics service predicts future service requests and triggers EAS instantiation in advance before the actual service request arrives. This preliminary action ensures the EAS is already available when needed, eliminating service delay and interruption while maintaining reliability.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If analytics service is integrated for predictive analytics, then service continuity is improved, but system complexity increases

Engineering Contradiction:

Improveservice continuityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

An analytics service is introduced as an intermediary component between the EEL and EAS infrastructure. This mediator performs predictive analytics and triggers instantiation decisions, centralizing the complexity in a dedicated service rather than distributing it across multiple EEL components, thereby managing system complexity while improving service continuity.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Speed

If proactive EAS instantiation is implemented, then service latency is reduced, but resource utilization efficiency decreases

Engineering Contradiction:

Improveservice latencyVSAvoidresource utilization

Core Design Contradiction:

SpeedVSLoss of energy

Solution Approach 1:

EAS instantiation is performed proactively based on analytics predictions of future service requests. By instantiating EAS instances in advance before actual demand arrives, the system reduces service latency and eliminates cold-start delays, while the predictive nature ensures resources are allocated based on forecasted needs rather than random provisioning.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250365207A1Methods, devices, and systems for analytics-enhanced edge enabling layer service continuity

Publication Date: 2025.11.27 INTERDIGITAL PATENT HOLDINGS INC

AI summary

Methods, devices, and systems for analytics-enhanced edge enabling layer service continuity are described herein. In one aspect, a method can include receiving, by an analytics service, an analytics request from an Edge Enabling Layer (EEL) entity to perform Application Context Relocation (ACR) detection; collecting, by the analytics service, analytics information related to the detection of ACR; generating, by the analytics service, an ACR detection notification according to the collected analytics information; and sending, by the analytics service, the ACR detection notification to one or more reporting targets.