Lapse: Latency & Power-Aware Placement of Data Stream Applications on Edge Computing

Data Stream Processing (DSP) systems have gained considerable attention in edge computing environments to handle data streams from diverse sources, notably IoT devices, in real-time at the network’s edge. However, their effective utilization concerning end-to-end processing latency, SLA violations, and infrastructure power consumption in heterogeneous environments depends on the adopted placement strategy, posing a significant challenge. This paper introduces Lapse, an innovative cost-based heuristic algorithm specifically crafted to optimize the placement of DSP applications within edge computing environments. Lapse aims to concurrently minimize latency SLA violations and curtail the overall power consumption of the underlying infrastructure. Simulation-driven experiments indicate that Lapse outperforms baseline strategies, substantially reducing the power consumption of the infrastructure by up to 24.42% and SLA violations by up to 75%.