ARQ-based Average Consensus over Unreliable Directed Network Topologies


In this paper, we address the problem of discrete-time average consensus, where agents (nodes) exchange information over unreliable communication links. We enhance the Robustified Ratio Consensus algorithm by exploiting features of the Automatic Repeat ReQuest (ARQ) protocol used for error control of data transmissions, in order to allow the agents to reach asymptotic average consensus even when operating within unreliable directed networks. This strategy, apart from handling time-varying delays induced by retransmissions of erroneous packets (which can be captured by the Robustified Ratio Consensus as well), can also handle packet drops that occur when exceeding a predefined packet retransmission limit imposed by the ARQ protocol. Invoking the ARQ protocol allows nodes to: (a) exploit the incoming error-free acknowledgement feedback signals to initially acquire or later update their out-degree, (b) know whether a packet has arrived or not, and (c) determine a local upper-bound on the delays which is imposed by the retransmission limit. By augmenting the network’s corresponding weighted adjacency matrix, to handle time-varying (yet bounded) delays and possible packet drops, we show that nodes can make use of the proposed algorithm, herein called the ARQ-based Ratio Consensus algorithm, to reach asymptotic average consensus, while maintaining low running sum values, despite the fact that the communication links are unreliable.

In arXiv Preprint
Evagoras Makridis
Evagoras Makridis
PhD Student in Distributed Decision and Control of Networked Systems

My research interests include autonomous systems in networks, distributed optimization, and data-driven sequential decision-making (Reinforcement Learning), with applications in quadrotor navigation, resource management, and wireless link adaptation and scheduling.