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Analytical Convergence Bounds of Distributed Intermittent Swarm Communication

Developed at: Worcester Polytechnic Institute

Project date: April, 2023

GitHub URL: parth-20-07/Analytical-Convergence-Bounds-of-Distributed-Intermittent-Swarm-Communication

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Brief Introduction on Project

In this project, we propose a deterministic threshold model for facilitating distributed intermittent swarm communication.

In our framework, each agent decides autonomously whether it will become a data mule, without a need for explicit network consensus.

Unlike existing approaches, this deterministic model allows each agent to independently evaluate lower bounds on the communication frequency, which can be used in decision-making processes. The newly devised threshold model guarantees that the optimal agent is selected to be a data mule concerning a user-defined multi-objective function and that the disjointed networks are connected infinitely often, over infinite time.

To demonstrate the optimally and versatility of the approach, the algorithm is tested on multiple swarm configurations with varying degrees of connectivity and packet frequency in the ARGoS simulation environment.