IP Library Granted Patent US 12,407,406
Granted Patent B2
US 12,407,406 · App. 17/651,940 · Granted Sep 2, 2025

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

Inventors: Shailendra Moyal (Pune, IN); Venkata Vara Prasad Karri (Visakhapatnam, IN); Sarbajit K. Rakshit (Kolkata, IN)
Assignee: International Business Machines Corporation
H04B7/18519G06N20/00H04B7/18513H04B7/18578
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Quick Facts
Patent No.
US 12,407,406
App. No.
17/651,940
Granted
Sep 2, 2025
Kind
B2
Abstract

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.

Claims (35)

1. A computer-implemented method (CIM) comprising:

receiving an edge computing satellite dataset including information indicative of (i) orbital information of a plurality of edge computing satellites devices in orbit around Earth, and (ii) edge computing capabilities of the plurality of edge computing satellite devices;

receiving a plurality of edge computing mobile consumption point datasets corresponding to a plurality of edge computing mobile consumption points, including a first edge computing mobile consumption point, where a given edge computing mobile consumption point dataset includes (i) transit information for the given edge computing mobile consumption point, and (ii) edge computing requirements of the given edge computing mobile consumption point;

determining, by machine logic, a predicted edge computing resources availability dataset corresponding to predicted availability of edge computing resources of the plurality of edge computing satellite devices based, at least in part, on: (i) the edge computing satellite dataset, and (ii) the plurality of edge computing mobile consumption point datasets; and

determining, by machine logic, a transit route from a current location of the first edge computing mobile consumption point to a destination location of the first edge computing mobile consumption point based, at least in part, on (i) the transit information of the first edge computing mobile consumption point, (ii) the edge computing requirements of the first edge computing mobile consumption point, and (iii) the predicted edge computing resources availability dataset.

2. The CIM of claim 1 , wherein the transit route corresponds to a transit route where the predicted edge computing resources availability dataset indicates that edge computing resources are predicted to be available at least sufficient to meet the edge computing requirements of the first edge computing mobile consumption point.

3. The CIM of claim 1 , wherein the edge computing capabilities of each satellite device of the plurality of edge computing satellite devices includes both units of computer processing and units of computer memory.

4. The CIM of claim 1 , wherein the edge computing mobile consumption points are selected from the group consisting of: (i) aircraft, (ii) aquatic vessels, (iii) automobiles, and (iv) spacecraft.

5. The CIM of claim 1 , wherein at least some of the plurality of edge computing satellite devices orbits the Earth at a low earth orbit.

6. The CIM of claim 1 , wherein the predicted edge computing resources availability dataset is determined, at least in part, by a machine learning model trained using historical edge computing satellites device usage datasets corresponding to historical usage of the plurality of edge computing satellites devices by edge computing mobile consumption points to output patterns of consumption of edge computing resources of the plurality of edge computing satellites devices by edge computing mobile consumption points.

7. A computer program product (CPP) comprising:

one or more computer-readable storage media; and

program instructions stored on the one or more computer-readable storage media to perform operations comprising:

receiving an edge computing satellite dataset including information indicative of (i) orbital information of a plurality of edge computing satellites devices in orbit around Earth, and (ii) edge computing capabilities of the plurality of edge computing satellite devices,

receiving a plurality of edge computing mobile consumption point datasets corresponding to a plurality of edge computing mobile consumption points, including a first edge computing mobile consumption point, where a given edge computing mobile consumption point dataset includes (i) transit information for the given edge computing mobile consumption point, and (ii) edge computing requirements of the given edge computing mobile consumption point,

determining, by machine logic, a predicted edge computing resources availability dataset corresponding to predicted availability of edge computing resources of the plurality of edge computing satellite devices based, at least in part, on: (i) the edge computing satellite dataset, and (ii) the plurality of edge computing mobile consumption point datasets, and

determining, by machine logic, a transit route from a current location of the first edge computing mobile consumption point to a destination location of the first edge computing mobile consumption point based, at least in part, on (i) the transit information of the first edge computing mobile consumption point, (ii) the edge computing requirements of the first edge computing mobile consumption point, and (iii) the predicted edge computing resources availability dataset.

8. The CPP of claim 7 , wherein the transit route corresponds to a transit route where the predicted edge computing resources availability dataset indicates that edge computing resources are predicted to be available at least sufficient to meet the edge computing requirements of the first edge computing mobile consumption point.

9. The CPP of claim 7 , wherein the edge computing capabilities of each satellite device of the plurality of edge computing satellite devices includes both units of computer processing and units of computer memory.

10. The CPP of claim 7 , wherein the edge computing mobile consumption points are selected from the group consisting of: (i) aircraft, (ii) aquatic vessels, (iii) automobiles, and (iv) spacecraft.

11. The CPP of claim 7 , wherein at least some of the plurality of edge computing satellite devices orbits the Earth at a low earth orbit.

12. The CPP of claim 7 , wherein the predicted edge computing resources availability dataset is determined, at least in part, by a machine learning model trained using historical edge computing satellites device usage datasets corresponding to historical usage of the plurality of edge computing satellites devices by edge computing mobile consumption points to output patterns of consumption of edge computing resources of the plurality of edge computing satellites devices by edge computing mobile consumption points.

13. A computer system (CS) comprising:

a processor set;

one or more computer-readable storage media; and

program instructions stored on the one or more computer-readable storage media to cause the processor set to perform operations comprising:

receiving an edge computing satellite dataset including information indicative of (i) orbital information of a plurality of edge computing satellites devices in orbit around Earth, and (ii) edge computing capabilities of the plurality of edge computing satellite devices,

receiving a plurality of edge computing mobile consumption point datasets corresponding to a plurality of edge computing mobile consumption points, including a first edge computing mobile consumption point, where a given edge computing mobile consumption point dataset includes (i) transit information for the given edge computing mobile consumption point, and (ii) edge computing requirements of the given edge computing mobile consumption point,

determining, by machine logic, a predicted edge computing resources availability dataset corresponding to predicted availability of edge computing resources of the plurality of edge computing satellite devices based, at least in part, on: (i) the edge computing satellite dataset, and (ii) the plurality of edge computing mobile consumption point datasets, and

determining, by machine logic, a transit route from a current location of the first edge computing mobile consumption point to a destination location of the first edge computing mobile consumption point based, at least in part, on (i) the transit information of the first edge computing mobile consumption point, (ii) the edge computing requirements of the first edge computing mobile consumption point, and (iii) the predicted edge computing resources availability dataset.

14. The CS of claim 13 , wherein the transit route corresponds to a transit route where the predicted edge computing resources availability dataset indicates that edge computing resources are predicted to be available at least sufficient to meet the edge computing requirements of the first edge computing mobile consumption point.

15. The CS of claim 13 , wherein the edge computing capabilities of each satellite device of the plurality of edge computing satellite devices includes both units of computer processing and units of computer memory.

16. The CS of claim 13 , wherein the edge computing mobile consumption points are selected from the group consisting of: (i) aircraft, (ii) aquatic vessels, (iii) automobiles, and (iv) spacecraft.

17. The CS of claim 13 , wherein at least some of the plurality of edge computing satellite devices orbits the Earth at a low earth orbit.

18. The CS of claim 13 , wherein the predicted edge computing resources availability dataset is determined, at least in part, by a machine learning model trained using historical edge computing satellites device usage datasets corresponding to historical usage of the plurality of edge computing satellites devices by edge computing mobile consumption points to output patterns of consumption of edge computing resources of the plurality of edge computing satellites devices by edge computing mobile consumption points.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2022
From: MOYAL, SHAILENDRA; RAKSHIT, SARBAJIT K.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 059075/0576 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2022
From: KARRI, VENKATA VARA PRASAD
To: IBM INDIA PRIVATE LIMITED
Reel/Frame 059075/0773 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2022
From: IBM INDIA PRIVATE LIMITED
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 059075/0847 →
Continuity (1)
Related Publication 20230268987A1 · Aug 24, 2023
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