Edge Framework for Cooperative Task Distribution

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Solution Overview

Problem

Existing automated systems face challenges in efficiently coordinating and controlling interconnected modules and hardware components, particularly in distributing computing tasks effectively across local and cloud-based systems.

Innovation Solution

A system comprising a broadcasting computing entity and multiple listening computing entities, where the broadcasting entity selects a functional operation and broadcasts a request, allowing capable listening entities to respond and perform the operation, with the output being transmitted back for further action.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Power

If a fully-cloud-based system is used where local devices perform minimal local processing and offload tasks to cloud services, then centralized processing capability is improved, but inter-network bandwidth requirements and system burden increase significantly

Engineering Contradiction:

Improvecentralized processing capabilityVSAvoidinter-network bandwidth requirements

Core Design Contradiction:

PowerVSLoss of energy

Solution Approach 1:

The system segments processing tasks into local and cloud components. Local devices perform routine processing independently, while the edge hub handles aggregation and coordination. This segmentation reduces the need for constant cloud communication, thereby reducing bandwidth requirements while maintaining centralized processing capability for complex tasks.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The edge hub serves as an intermediary between local devices and cloud services. It performs local aggregation, preprocessing, and coordination of tasks, reducing the volume of data that needs to be transmitted to the cloud. This intermediary approach maintains centralized processing capability while significantly reducing inter-network bandwidth requirements.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of energy

If edge systems perform most routine processing tasks within the local subsystem, then inter-network bandwidth requirements are reduced, but coordination complexity between multiple computing entities increases

Engineering Contradiction:

Improveinter-network bandwidth requirementsVSAvoidcoordination complexity

Core Design Contradiction:

Loss of energyVSDevice complexity

Solution Approach 1:

The edge hub is designed with multi-functionality, handling task coordination, data aggregation, local processing, and cloud communication. This universal approach consolidates coordination functions in a single entity, reducing the overall coordination complexity that would otherwise exist across multiple distributed devices.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

Local devices are equipped with self-service capabilities to perform routine processing tasks independently without requiring constant coordination with other entities. This autonomy reduces the coordination burden on the edge hub and simplifies the overall system coordination complexity.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If custom code is required to coordinate and control interconnected modules in automated systems, then system functionality is improved, but development time and complexity increase

Engineering Contradiction:

Improvesystem functionalityVSAvoiddevelopment time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system uses templates and predefined coordination patterns that can be copied and adapted for different automated system configurations. Instead of writing custom coordination code from scratch, developers can replicate proven patterns, significantly reducing development time while maintaining system functionality and adaptability.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system allows configuration through parameter changes rather than code modifications. By adjusting parameters and settings in the predefined coordination framework, the system can adapt to different functionalities and requirements without requiring custom code development, thus reducing development time while maintaining versatility.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12265809B2Scalable cross-boundary edge framework

Publication Date: 2025.04.01 INSIGHT DIRECT USA INC

AI summary

Apparatus and associated methods relate to automating building of a software solution that is cooperatively performed. A broadcasting computing entity selects a functional operation from a set of one or more functional operations associated with the software solution and then broadcasts a request to perform the functional operation selected. Each of a plurality of listening computing entities connected to the network receives the request to perform the functional operation and determines capability of performing the functional operation. A capable one of the plurality of listening computing entities that determines itself capable of performing the functional operation transmits a response to the request received indicating capability of performing the functional operation and performs the functional operation, thereby generating the output of the functional operation, which is transmitted to the broadcasting computing entity. The broadcasting computing entity then performs an action using the output of the functional operation received.