Distributed Data Handling Nodes Reduce Latency in Space Networks
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Solution Overview
Problem
Current data communication systems, such as those following CCSDS protocols, often experience data latency of up to three hours due to the processing of data from a single source, which can lead to inefficiencies and inaccuracies in data delivery, particularly in space-to-ground communication systems like NASA's EOS.
Innovation Solution
A distributed communication network system that includes data-handling nodes capable of receiving and processing multiple data streams in real-time, removing redundancies, correcting misconfigurations, and generating cohesive data streams, which can handle high-rate CCSDS-encoded data from multiple sources, ensuring proper ordering and reducing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single ground station receives data from a single data source, then the system structure is simple, but data latency increases to up to three hours
Solution Approach 1:
The system segments the centralized data processing architecture into multiple distributed data-handling nodes (DHNs) located at different ground stations. Each DHN independently processes data units from multiple sources, enabling parallel processing and reducing overall data latency while maintaining manageable complexity through modular design.
Solution Approach 2:
The system transitions from a single-dimensional centralized processing model to a multi-dimensional distributed network architecture. Data units can travel through multiple paths and dimensions simultaneously, allowing data to reach processing facilities faster by selecting optimal routes and enabling concurrent processing at multiple nodes.
2Reliability
If data is received from multiple sources, then data availability improves, but data ordering and redundancy management become more complex
Solution Approach 1:
Data units are pre-tagged with identification information (source ID, sequence numbers, timestamps) before transmission. This preliminary action enables receiving DHNs to automatically perform ordering, deduplication, and validation operations without complex real-time processing, reducing processing complexity while maintaining high data availability from multiple sources.
Solution Approach 2:
The system implements feedback mechanisms where DHNs monitor incoming data units, detect redundancies, and generate control signals to request retransmission of missing or corrupted data. This feedback loop automatically manages data integrity and ordering from multiple sources without requiring complex manual intervention.
3Loss of time
If real-time processing is implemented, then data latency is reduced, but system complexity and processing requirements increase
Solution Approach 1:
Each data-handling node operates autonomously to perform self-service functions including data validation, ordering, redundancy removal, and error detection. This distributes processing intelligence across multiple nodes rather than concentrating complexity in a central system, enabling real-time processing while keeping individual node complexity manageable.
Solution Approach 2:
The system changes key processing parameters by implementing configurable data unit sizes, transmission rates, and processing thresholds. These parameter adjustments optimize real-time processing performance while balancing system complexity, allowing the architecture to adapt to different operational requirements without proportional increases in complexity.
Data Source
AI summary
In one embodiment, a system for data handling in a distributed communication network includes one or more data-handling nodes (DHNs) each residing at one of one or more centrals that are each operable to receive a stream of first data units from a routing system. The stream of first data units includes both stored mission data (SMD) and telemetry data having originated at one or more remote units. Each DHN is operable, in near real time, to remove redundant instances of first data units from the stream of first data units, properly order first data units in the stream of first data units received at the central out of order, remove misconfigured first data units from the stream of first data units, extract the SMD from the stream of first data units, generate second data units from the extracted SMD, and communicate a stream of the second data units to one or more interface data processors (IDPs).