AtoNet: An Adaptive Distributed Algorithm for Dynamic Topology Management in Decentralized IoT Networks

Abstract

The increasing complexity of decentralized IoT and edge environments requires systems capable of real-time topological self-organization, autonomous role assignment, and adaptive resilience under dynamic and unpredictable conditions. However, current approaches often rely on static structures, centralized orchestration, or periodic reevaluation, limiting their scalability and robustness. In this work, we propose AtoNet, a fully decentralized and adaptive algorithm for dynamic topology management in IoT networks. AtoNet leverages behavioral validation, trust-based role assignment, and inter-agent coordination to ensure resilient structure formation and secure, autonomous operation. The system includes real-time event detection, fault tolerance via heartbeat-based monitoring, and local topology reconfiguration triggered by trust decay or network stress. Experimental simulations demonstrate that AtoNet maintains low latency, high throughput, and fast adaptation rates, even in highly volatile or congested scenarios, highlighting its potential applicability in decentralized edge-IoT contexts.