Latency-based Vector Scheduling of Many-task Applications for a Hybrid Cloud

A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. We have previously demonstrated that a de-centralized vector scheduling approach based on performance measurements can be used successfully for this task placement scena...

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Bibliographic Details
Published inIEEE ... International Conference on Cloud Computing pp. 257 - 262
Main Authors Mithila, Shifat P., Baumgartner, Gerald
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2022
Subjects
Cloud computing
Cloud middleware
Decentralized scheduling
Many-task computing
Measurement
Middleware
Processor scheduling
Resource management
Scheduling
Task analysis
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Summary:A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. We have previously demonstrated that a de-centralized vector scheduling approach based on performance measurements can be used successfully for this task placement scenario. In this paper, we extend this approach to task placement based on latency measurements. Each node collects the performance measurements from its neighbors on an overlay graph, measures the communication latency, and then makes local decisions on where to move tasks. We present a centralized algorithm for configuring the overlay graph based on latency measurements and extend the vector scheduling approach to take latency into considerations. Our experiments in CloudLab demonstrate that this approach results in better performance and resource utilization than without latency information.
ISSN:2159-6190
DOI:10.1109/CLOUD55607.2022.00047