Optimizing Communication Strategies in Contested and Dynamic Environments
Claudia Szabo, Vanja Radenovic, Gregory Judd, Dustin Craggs, Kin Leong Lee, Xiaoshan Chen, Kevin Chan · 2020
Contested and dynamic environments such as those of military operations and crisis situations have poor and unreliable network conditions and participants usually only have an incomplete, local, and quickly changing view of the system. In such systems, optimizing how nodes communicate such that important messages arrive in a timely manner without degrading network performance is critical. SMARTNet is a middleware that prioritizes and controls the messages sent by each node, with the aim of preserving network bandwidth, while at the same time achieving timely delivery of messages within a contested and dynamic environment. In this industry experience report, we propose the integration of evolutionary algorithms with the SMARTNet middleware allowing it to learn the best bandwidth ratio for each different message type. We propose a centralized integration, where a single node performs the evolutionary algorithm (EA) and determines a communication strategy that is subsequently followed by all SMARTNet nodes. Our results show an improvement of nearly 50% over the baseline, at a cost of significant pre-run preparation for the EA to converge on a potential solution. Our analysis also shows the benefits of using an application-specific metric as an objective of the EA, and our discussion identifies new research avenues.