Kairos: a self-configuring approach for short and accurate event timeouts in IoT

Abstract

The Internet of Things (IoT) consists of embedded sensors that transmit events over a wireless network. Complex event processing provides powerful abstractions to aggregate and analyze relationships among event streams in real time, which can improve IoT application development and management. A key challenge are stream imperfections, because of the non-deterministic nature of IoT: events can be delayed due to variance in delay, or may even be missing due to packet loss. Timeouts are used to handle stream imperfections, distinguishing between delayed and lost events. For some applications, missing delayed events is costly, as the quality of the result depends on the presence of all inputs, but reacting too late to event non-arrivals can also lead to incorrect results. State-of-the-art results in timeouts that are impractically large when little to no missed events are tolerated by the application. We propose Kairos, a novel, self-configuring technique for determining event arrival timeouts in IoT that are both small and ensure that little to no events are missed, while also eliminating the overhead and complexity of user configuration. We evaluate our approach against the state-of-the-art using two representative IoT networks: SmartMesh IP and LoRaWAN. The results show that our solution is capable of reducing timeouts by up to two orders of magnitude even when little to no missed events are tolerated, thus satisfying the aforementioned application requirements.