Fault Detection in Distributed Computing via Peer Data Verification
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Solution Overview
Problem
Existing peer-hosted and peer-to-peer networks are vulnerable to disruptions and data tampering due to centralized authority, making them susceptible to hacking and cheating.
Innovation Solution
A distributed computing network system that employs multiple peer computing devices and a management server to manage authority information, where each peer device communicates with others to verify dataset integrity and detects faults by comparing instances of data sets, sending fault messages to the management server when discrepancies are found, and updates authority information to mitigate faults.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If centralized authority is used in peer-hosted networks and peer-to-peer networks, then data management is simplified and authority control is concentrated, but the network becomes vulnerable to disruptions by bad peers and susceptible to hacking or cheating
Solution Approach 1:
The patent divides centralized authority into multiple distributed authorities (first authority, second authority, third authority) that each manage different data sets. This segmentation eliminates the single point of failure in centralized systems while maintaining manageable authority control through modular distribution across multiple peer computing devices.
Solution Approach 2:
The patent introduces an arbitration mechanism that acts as an intermediary when authority conflicts or faults occur. The arbitration logic resolves disputes between multiple authorities and determines which data instance is correct, providing a mediator that maintains system reliability without requiring a single centralized authority.
2Reliability
If multiple authorities are distributed across peer computing devices, then network security and fault tolerance are improved, but system complexity increases
Solution Approach 1:
Authority management is segmented into discrete, independent authority instances (first authority, second authority, third authority) each responsible for specific data sets. This segmentation simplifies complexity by creating modular, manageable units rather than a monolithic complex system.
Solution Approach 2:
The system changes the parameter of authority distribution from centralized to multi-authority distributed. Each authority has defined parameters (data set ownership, fault detection thresholds) that automate complexity management through configurable rules rather than complex procedural logic.
3Measurement precision
If data instances are compared across multiple peer computing devices, then data integrity and fault detection are enhanced, but communication overhead and processing time increase
Solution Approach 1:
Peer computing devices continuously maintain and compare data instances in advance before faults occur. This preliminary action ensures data integrity is verified proactively rather than reactively, reducing the time needed for fault detection when discrepancies actually occur.
Solution Approach 2:
The system implements continuous feedback loops where peer devices monitor data instances, compare them against authorities, and report discrepancies. This feedback mechanism enables real-time fault detection without requiring extensive communication overhead by only activating when anomalies are detected.
Data Source
AI summary
The present disclosure provides methods for detecting faults in a distributed computing network system. The method includes receiving, from a management services, authority information identifying peer computing devices of a distributed computing network system. For each respective peer computing device, a first message comprising a first instance of a dataset and a second message comprising a second instance of the dataset are received. Where the first peer computing device and the second peer computing device have authority over the data set, it is determined whether the first instance of the dataset matches the second instance of the dataset. Where the first instance of the dataset does not match the second instance of the dataset, a fault message is sent to the management services indicating that a fault has been detected at the first peer computing device.