Multi-objective optimisation strategy for on-orbit fault-tolerant decision making

Cowlishaw, Robert and Arulselvan, Ashwin and Riccardi, Annalisa (2024) Multi-objective optimisation strategy for on-orbit fault-tolerant decision making. In: 2024 IEEE World Congress on Computational Intelligence (WCCI), 2024-06-30 - 2024-07-05.

[thumbnail of FCowlishaw-etal-WCCI-2024-Multi-objective-optimisation-strategy-for-on-orbit-fault-tolerant-decision-making]
Preview
 Text. Filename: Cowlishaw-etal-WCCI-2024-Multi-objective-optimisation-strategy-for-on-orbit-fault-tolerant-decision-making.pdf
Accepted Author Manuscript
License: Creative Commons Attribution 4.0 logo
Download (935kB)| Preview

Abstract

With an increasing number of satellites in orbit, consensus across a heterogeneous group of satellites can lead to a more neutral, unbiased, and accurate decisions. Fault tolerant consensus algorithms such as Practical Byzantine Fault Tolerance (pBFT) require communication with all other network members up to 4 times. In a network with thousands of satellites in space on different trajectories, this time can approach millennia. Therefore, identifying a subset of satellites that can form a sub-network able to converge to a consensus decision in a useful time window, while maximising the number of members to increase consensus accuracy and trustworthiness, can be formulated as a multi-objective combinatorial optimisation problem. The problem is explained and defined with the optimisation method and the consensus algorithm steps described. Metrics for measuring the output of the optimal pareto front are considered and applied to the front computed. The real satellite positions used generate a non-fixed topology and high latency scenario such as that of a real on-orbit decision being made. The trend shown over 100 days of satellite positions propagation with up to 82 International Charter: Space and Major Disasters satellites shows up to 22 satellites can be used in a subset with a near linear increase in consensus time along the optimal pareto front and exponential trend for the mean values computed over 100 runs of the NSGA-II algorithm. The minimum consensus time is found to be 47 minutes for a subset of 4 satellites for the given time frame.

ORCID iDs

Cowlishaw, Robert, Arulselvan, Ashwin ORCID logoORCID: https://orcid.org/0000-0001-9772-5523 and Riccardi, Annalisa ORCID logoORCID: https://orcid.org/0000-0001-5305-9450;
CORE (COnnecting REpositories)