Orbital Edge Computing Routes for Mobile Resource Availability

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Solution Overview

Problem

Existing edge computing systems face challenges in efficiently managing the availability and distribution of resources among orbiting edge computing devices and mobile consumption points, particularly in low Earth orbit (LEO) satellite environments, leading to potential bottlenecks and insufficient resource allocation.

Innovation Solution

A method and system that utilize machine logic to determine predicted availability of edge computing resources by analyzing datasets of satellite positions and consumption points, and dynamically adjust transit routes to ensure sufficient resource availability, including handoffs between satellites and rerouting of consumption points to optimize resource allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If edge computing resources are dynamically allocated to mobile consumption points, then resource availability is improved, but system complexity increases due to continuous route optimization and handoff coordination

Engineering Contradiction:

Improveresource availabilityVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-calculating optimal transit routes and predicting resource availability before actual consumption occurs. The machine logic analyzes satellite positions, orbital mechanics, and consumption point trajectories to determine future resource availability and pre-establish handoff protocols, reducing the complexity of real-time decision-making.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

An intermediary machine logic layer is introduced between the edge computing satellites and mobile consumption points. This intermediary layer handles the complex coordination of resource allocation, route optimization, and handoff management, shielding the consumption points from system complexity while ensuring reliable resource delivery.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If transit routes are dynamically optimized based on satellite positions, then resource allocation efficiency is improved, but computational overhead increases

Engineering Contradiction:

Improveresource allocation efficiencyVSAvoidcomputational overhead

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary computational analysis by pre-calculating optimal routes and predicting resource availability based on known satellite orbital mechanics and consumption point trajectories. This advance computation reduces the need for continuous real-time calculations, lowering overall computational overhead while maintaining high allocation efficiency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system leverages the natural movement patterns of satellites in orbit and the predictable trajectories of mobile consumption points to enable self-optimizing resource allocation. By exploiting these inherent patterns rather than continuously calculating optimal routes, the system reduces computational overhead while maintaining efficiency.

Inventive Principle:

Principle #25Self-service

3Reliability

If continuous handoffs between satellites are implemented, then service continuity is improved, but coordination complexity increases

Engineering Contradiction:

Improveservice continuityVSAvoidcoordination complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary coordination by pre-determining handoff protocols and identifying optimal handoff timing based on predicted satellite positions and consumption point trajectories. This advance planning ensures continuous service while reducing the complexity of real-time coordination by establishing handoff rules beforehand.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms where machine logic continuously monitors resource availability and consumption patterns, adjusting handoff protocols accordingly. This feedback loop enables the system to learn from past handoffs and optimize future coordination, reducing complexity through adaptive management.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12407406B2Transit routes with orbital edge computing resource availability for mobile edge computing consumption points

Publication Date: 2025.09.02 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Disclosed are techniques to determine navigation paths for mobile points of consumption of edge computing resources where the edge computing resources are at least partially hosted on satellite devices. Datasets corresponding to a set of edge computing satellites are received describing their positions, orbital paths, and edge computing resources. Further datasets are received corresponding to mobile points of consumption of edge computing resources. Using both datasets, predictions are determined corresponding to demand for edge computing resources of the edge computing satellites. When a new mobile point of consumption of edge computing resources queues up a transit route to a destination, that transit route and the accompanying requirement for edge computing resources is compared with the determined predictions of resource availability. Where sufficient edge computing resources are unavailable for a transit route, a new route is generated to transit through regions where sufficient edge computing resources are predicted to be available.