RACER: A Lightweight Distributed Consensus Algorithm for the IoT with Peer-Assisted Latency-Aware Traffic Optimisation

Internet-of-Things (IoT) devices are interconnected objects embedded with sensors and software, enabling data collection and exchange. These devices encompass a wide range of applications, from household appliances to industrial systems, designed to enhance connectivity and automation. In distributed IoT networks, achieving reliable decision-making necessitates robust consensus mechanisms that allow devices to agree on a shared state of truth without reliance on central authorities. Such mechanisms are critical for ensuring system resilience under diverse operational conditions. Recent research has identified three common limitations in existing consensus mechanisms for IoT environments: dependence on synchronised networks and clocks, reliance on centralised coordinators, and suboptimal performance. To address these challenges, this paper introduces a novel consensus mechanism called Randomised Asynchronous Consensus with Efficient Real-time Sampling (RACER). The RACER framework eliminates the need for synchronised networks and clocks by implementing the Sequenced Probabilistic Double Echo (SPDE) algorithm, which operates asynchronously without timing assumptions. Furthermore, to mitigate the reliance on centralised coordinators, RACER leverages the SPDE gossip protocol, which inherently requires no leaders, combined with a lightweight transaction ordering mechanism optimised for IoT sensor networks. Rather than using a blockchain for transaction ordering, we opted for an eventually consistent transaction ordering mechanism to specifically deal with high churn, asynchronous networks and to allow devices to independently and deterministically order transactions. To enhance the throughput of IoT networks, this paper also proposes a complementary algorithm, Peer-assisted Latency-Aware Traffic Optimisation (PLATO), designed to maximise efficiency within RACER-based systems. The combination of RACER and PLATO is able to maintain a throughput of above 600 mb/s on a 100-node network, significantly outperforming the compared consensus mechanisms in terms of network node size and performance.