Authors:
Carlos Kayser
1
;
Marcos Dias de Assunção
2
and
Tiago Ferreto
1
Affiliations:
1
School of Technology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
;
2
Dept. of Software Engineering and IT, École de Technologie Supérieure, Univ. of Quebec, Montreal, Canada
Keyword(s):
Stream Processing, Edge Computing, Scheduling, Power Consumption, Service Level Agreement (SLA).
Abstract:
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%.