Publikation

An Energy-Efficient Stream Join for the Internet of Things

Philipp M. Grulich Adrian Michalke

In: International Workshop on Data Management on New Hardware. International Workshop on Data Management on New Hardware (DaMoN-2021) Seiten 1-8 8 International Workshop on Data Management on New Hardware 2021.

Abstrakt

The Internet of Things (IoT) combines large data centers with (mobile, networked) edge devices that are constrained both in compute power and energy budget. Modern edge devices contribute to query processing by leveraging accelerated processing units with multicore CPUs or GPUs. Therefore, data processing in the IoT presents the challenges of 1) minimizing the energy consumed while sustaining a given query throughput, and 2) processing increasingly complex queries within a given energy budget. In this paper, we investigate how modern edge devices can reduce the energy requirements of stream joins as a common data processing operation. We explore three dimensions to save energy: workload characteristics, computational efficiency, and heterogeneous hardware. Based on our findings, we propose the ecoJoin that 1) reduces energy consumption by 81% at a given join throughput, and 2) enables scaling the throughput by two orders-of-magnitude within a given energy budget.

Projekte

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence