Orbital Edge Computing Nanosatellite Latency Reduction
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Solution Overview
Problem
The existing bent-pipe architecture for satellite constellations is limited by high downlink latencies, high latency in data processing, and the need for extensive ground infrastructure, which becomes a bottleneck as the constellation population increases, especially due to limitations in link availability, bitrate, and energy constraints.
Innovation Solution
The Orbital Edge Computing (OEC) system enables edge computing on each nanosatellite, allowing data to be processed locally and organizing satellites into computational pipelines that parallelize data collection and processing, reducing reliance on ground stations and leveraging formation flying techniques to manage energy and latency constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a bent-pipe architecture is used for satellite constellations, then ground infrastructure can be established, but downlink latency and data processing latency increase significantly
Solution Approach 1:
The patent implements preliminary action by enabling satellites to process data locally before downlinking. Edge computing nodes on satellites perform data processing, filtering, and aggregation in advance, so that when downlink opportunities arise, only processed or prioritized data needs to be transmitted, significantly reducing effective latency despite the bent-pipe architecture remaining in place
Solution Approach 2:
The patent introduces an intermediary layer (edge computing nodes) between the sensor data source and the ground infrastructure. This intermediary performs local processing, data aggregation, and intelligent routing decisions, reducing the amount of data that must be transmitted through the bent-pipe architecture and thereby reducing overall system latency
2Productivity
If constellation population increases, then observation coverage and temporal resolution improve, but communication bandwidth requirements exceed ground station capabilities
Solution Approach 1:
The patent applies segmentation by dividing the constellation into distributed edge computing nodes that independently process data locally. Each satellite processes its own data and data from neighboring satellites, segmenting the overall data processing workload across multiple independent nodes rather than requiring all data to be transmitted to ground stations
Solution Approach 2:
The patent combines multiple functions (data processing, filtering, aggregation, and routing) at the edge computing nodes on satellites. This merging of functions reduces the total data volume that needs to be transmitted to ground stations by processing and consolidating data before transmission
3Productivity
If more ground stations are deployed to support larger constellations, then data downlink capacity increases, but system complexity and infrastructure cost increase
Solution Approach 1:
The patent implements self-service by enabling satellites to perform data processing and routing decisions autonomously at the edge. Satellites with edge computing nodes make intelligent decisions about which data to downlink and when, reducing their dependence on ground station infrastructure and thereby reducing the number and complexity of ground stations required
4Measurement precision
If data is processed at ground stations, then comprehensive processing can be performed, but processing latency increases due to downlink requirements
Solution Approach 1:
The patent performs preliminary data processing at edge computing nodes on satellites before data leaves orbit. This preliminary processing includes filtering, aggregation, and initial analysis, so that when data is downlinked to ground stations, further processing can continue without the initial delay of transmitting raw data, thereby reducing overall processing latency while maintaining comprehensive processing capability
Data Source
AI summary
A system and method of controlling a constellation of nanosatellites colocates processing resources with sensors in each satellite. Latencies in data transmission are addressed by organizing the constellation of satellites into computational pipelines. An orbital edge computing module simulates system design for mission design, planning and analysis in addition to supporting online autonomy.