TY - GEN
T1 - Lapse
T2 - 14th International Conference on Cloud Computing and Services Science, CLOSER 2024
AU - Kayser, Carlos Henrique
AU - de Assunção, Marcos Dias
AU - Ferreto, Tiago
N1 - Publisher Copyright:
© 2024 by SCITEPRESS – Science and Technology Publications, Lda.
PY - 2024
Y1 - 2024
N2 - 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%.
AB - 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%.
KW - Edge Computing
KW - Power Consumption
KW - Scheduling
KW - Service Level Agreement (SLA)
KW - Stream Processing
UR - https://www.scopus.com/pages/publications/85194169151
U2 - 10.5220/0012737400003711
DO - 10.5220/0012737400003711
M3 - Contribution to conference proceedings
AN - SCOPUS:85194169151
T3 - International Conference on Cloud Computing and Services Science, CLOSER - Proceedings
SP - 358
EP - 366
BT - Proceedings of the 14th International Conference on Cloud Computing and Services Science, CLOSER 2024
A2 - van Steen, Maarten
A2 - Pahl, Claus
PB - Science and Technology Publications, Lda
Y2 - 2 May 2024 through 4 May 2024
ER -