Distributed Average Consensus for Verifying Node Participation
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Solution Overview
Problem
Existing distributed computing methods fail to accurately verify if all participating devices have contributed to the computation, leading to potential compensation for non-performing devices, as they can converge without actual participation.
Innovation Solution
The implementation of a distributed average consensus (DAC) algorithm, where devices exchange results in a peer-to-peer fashion, repeatedly form connections, and calculate an average to confirm each device's contribution, ensuring consensus without the need for additional routing protocols or overlay topologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If typical distributed computing operations use fault-tolerant techniques to allow convergence, then the system can tolerate non-participating devices, but the convergence result cannot indicate whether computing devices actually participated in the computation
Solution Approach 1:
The patent implements a feedback mechanism where each computing device reports its partial result to the coordinator, and the coordinator verifies participation by checking if the sum of reported partial results matches the expected computation result. This feedback loop enables both fault tolerance and accurate participation verification simultaneously.
Solution Approach 2:
The patent introduces a coordinator as an intermediary that collects partial results from distributed computing devices, verifies their participation, and combines results to produce the final computation outcome. The coordinator acts as a mediator that enables both fault-tolerant operation and accurate verification of device participation.
2Measurement precision
If distributed computing devices exchange results in peer-to-peer fashion and perform consensus algorithm, then participation can be confirmed, but additional routing protocols or overlay topologies are required
Solution Approach 1:
The patent extracts the coordination and verification functions from the peer-to-peer consensus mechanism and consolidates them in a central coordinator. This removes the need for complex routing protocols and overlay topologies, as the coordinator directly collects and verifies results from all computing devices through simplified communication channels.
Data Source
AI summary
Each of a plurality of distributed computing devices receives a respective data partition of a plurality of data partitions for a computing task. A first distributed computing device generates a first partial result of a plurality of partial results generated by the plurality of distributed computing devices. The first computing device iteratively executes a distributed average consensus (DAC) process. At each iteration, the first computing device transmits the first partial result to a second computing device, receives a second partial result generated by the second computing device, and updates the first partial result by computing an average of the first and second partial results. In response to determining that respective partial results of the plurality of distributed computing devices have reached a consensus value, the first computing device stops executing the DAC process, and generates a final result of the computing task based on the consensus value.