Satellite Edge Compute Clustering for Low-Latency Access
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Solution Overview
Problem
Satellite communication systems face challenges in providing low-latency access to compute resources due to the dynamic and changing environment of satellites, including thermal conditions, radiation events, and orbital movements, which differ significantly from terrestrial cloud computing environments.
Innovation Solution
A method and system for managing access to compute resources on a group of satellites, involving a satellite control system that receives requests, routes them based on energy status, thermal conditions, and orbital data, and dynamically clusters satellites to provide low-latency endpoint-to-endpoint communication channels, using laser connections and intelligent load balancing to ensure availability and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If compute resources are provided from ground-based systems via satellite communication, then service coverage is extended to remote areas, but latency increases due to the round-trip communication path
Solution Approach 1:
The patent moves compute resources from the ground dimension to the orbital dimension by deploying satellite-based computing platforms. This spatial relocation enables processing to occur closer to end users, transforming the traditional ground-up communication model into a distributed space-ground hybrid architecture that reduces latency while maintaining broad coverage
Solution Approach 2:
The patent introduces satellite-based edge computing nodes as intermediaries between ground-based data centers and remote users. These intermediary satellites host computing environments that can directly process requests without requiring constant ground communication, thereby reducing latency while maintaining service coverage
2Reliability
If satellites are dynamically clustered to provide compute resources, then service quality and latency are improved, but system complexity increases
Solution Approach 1:
The patent implements dynamic satellite clustering where groups of satellites are reconfigured in real-time based on service demands, thermal conditions, and orbital positions. This dynamic reorganization allows the system to optimize performance and latency by bringing compute resources closer to users while adapting to changing environmental constraints
Solution Approach 2:
The patent segments the satellite constellation into multiple independent computing clusters, each capable of autonomous operation. This segmentation allows complex satellite groups to be managed as smaller, more manageable units with dedicated control logic, reducing overall system complexity while maintaining service quality
3Reliability
If compute resources are distributed across multiple satellites, then availability and reliability are improved, but system complexity and coordination overhead increase
Solution Approach 1:
The patent merges multiple satellite compute resources into unified virtualized environments that can be accessed as single logical units. This consolidation allows distributed resources to be managed through centralized orchestration layers, improving availability through redundancy while reducing coordination complexity through abstraction
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient and low-latency delivery of compute resources, such as data and applications, directly from satellites to user terminals, reducing latency and improving service quality by dynamically adapting to the unique conditions of the satellite environment.
Implementation Method 1
The satellite and the ground station transmit and receive signals via a respective satellite antenna and a ground station antenna
Data Source
AI summary
A satellite includes a satellite control system, an antenna connected to the satellite control system, a memory device, a computing environment configured on the satellite. The satellite can be part of a cluster of satellites that are dynamically organized from a larger group of satellites based on one or more of scheduled workload, a movement of the larger group of satellites, thermal issues, reset or reboot issues, energy issues and capabilities of individual satellites to provide access to compute resources on the cluster of satellites such as cloud-services or data. Requests for compute resources can be routed to the proper satellite in the dynamically-changing cluster of satellites to provide data associated with the compute resources or access to functions associated with the compute resources such as stock, bond, or cryptocurrency trading functions. The cluster of satellites can be periodically updated to provide continued service or availability of the compute resources.


