Resilient and Decentralized Control of Multi-level Cooperative Mobile Networks to Maintain Connectivity under Adversarial Environment

TL;DR

This paper presents a game-theoretic, decentralized control algorithm for multi-level mobile networks that enhances connectivity and resilience against adversarial attacks, with proven convergence and robustness demonstrated through case studies.

Contribution

It introduces a novel decentralized algorithm for maximizing network connectivity in multi-level networks, with convergence to Nash equilibrium and resilience analysis under adversarial attacks.

Findings

Algorithm converges to Nash equilibrium asymptotically.

Network maintains connectivity under adversarial attacks.

Case studies validate effectiveness and inter-layer resilience.

Abstract

Network connectivity plays an important role in the information exchange between different agents in the multi-level networks. In this paper, we establish a game-theoretic framework to capture the uncoordinated nature of the decision-making at different layers of the multi-level networks. Specifically, we design a decentralized algorithm that aims to maximize the algebraic connectivity of the global network iteratively. In addition, we show that the designed algorithm converges to a Nash equilibrium asymptotically and yields an equilibrium network. To study the network resiliency, we introduce three adversarial attack models and characterize their worst-case impacts on the network performance. Case studies based on a two-layer mobile robotic network are used to corroborate the effectiveness and resiliency of the proposed algorithm and show the interdependency between different layers of the network during the recovery processes.