Edge Device Constellation Attestation via Blockchain
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Solution Overview
Problem
In edge computing environments, generating trustworthy information in real-time and at scale is challenging due to the large volume and variety of data from multiple sources, particularly in scenarios like edge deployments and fog computing, where data is generated rapidly by sensors, and ensuring the trustworthiness of this information is non-trivial.
Innovation Solution
A hardware-accelerated constellation of edge devices is used, where each device validates events across others, with digitally signed timestamps, and a blockchain is employed to attest any event generated within the constellation, allowing third-party verification, and each device monitors latency to determine the origination and identity of other devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a hardware-accelerated constellation of edge devices is used to validate events across multiple devices with digitally signed timestamps, then the reliability and trustworthiness of generated information is improved, but the device complexity and computational overhead increase
Solution Approach 1:
The system segments the trust validation process into distributed edge devices, where each device independently validates events from other devices. This segmentation allows the system to achieve high reliability through distributed verification while managing complexity by dividing the overall validation task across multiple independent nodes rather than requiring a single complex centralized system.
Solution Approach 2:
Blockchain technology serves as an intermediary layer that mediates between edge devices and third-party verifiers. The blockchain network handles the complex tasks of timestamp validation, digital signature verification, and event ordering, allowing individual edge devices to maintain relatively simple local validation logic while still achieving high overall system reliability.
2Reliability
If real-time validation of events across multiple edge devices is performed with digital signatures and blockchain attestation, then the authenticity and integrity of data are ensured, but the processing time and latency increase
Solution Approach 1:
Edge devices perform preliminary validation of incoming events by checking digital signatures and verifying timestamps against the blockchain before full processing occurs. This preliminary action filters out obviously invalid events early in the process, reducing the time required for comprehensive validation while maintaining high standards for data authenticity and integrity.
Solution Approach 2:
The system maintains continuous synchronization with the blockchain network, with edge devices constantly updated on the latest validated events and timestamps. This continuous operation eliminates the need for periodic re-synchronization and allows devices to perform validation operations continuously with minimal interruption, reducing overall processing time while ensuring data integrity.
3Adaptability or versatility
If a blockchain is employed to attest events generated within the constellation, then third-party verification capability is enabled, but the quantity of data to be processed and stored increases
Solution Approach 1:
The system extracts only the essential verification elements (digital signatures, timestamps, and event hashes) to the blockchain, while keeping the full event data distributed locally across edge devices. This extraction approach enables third-party verification of event authenticity through the blockchain without requiring third parties to process or store the complete volume of raw event data, thus reducing the data burden while maintaining verification capability.
Solution Approach 2:
Instead of storing complete event data on the blockchain, the system stores cryptographic hashes and references that act as compact copies or representations of the full events. These cryptographic copies are sufficient for verification purposes but occupy minimal space, enabling widespread third-party verification without proportionally increasing data storage requirements across the network.
4Measurement precision
If each edge device monitors latency to determine origination and identity of other devices, then measurement precision of device identity is improved, but the use of energy and computational resources increases
Solution Approach 1:
Edge devices autonomously monitor and measure latency to other devices without requiring external coordination or additional infrastructure. Each device independently performs timing measurements and uses these measurements to determine device identity and origination, eliminating the need for centralized identity management systems and reducing overall energy consumption while maintaining high measurement precision.
Data Source
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AI summary
Methods, apparatus, systems, and articles of manufacture for attestation for a constellation of edge devices are disclosed. An example first edge computing node includes at least one memory, instructions in the first edge computing node, and processor circuitry to execute the instructions to record one or more timestamps corresponding to processing of event data from a first edge computing device, transmit the event data and the one or more timestamps to a second edge computing node, in response to the second edge computing node validating the event data based on the one or more timestamps and historical key performance indicators corresponding to the first edge computing node, validate the event data.