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Join the Best Queue: Reducing Performance Variability in Heterogeneous Systems

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Spicuglia Sebastiano, Chen Lydia, Binder Walter,
Project LoadOpt - Workload Characterization and Optimization for Multicore Systems
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Proceedings (peer-reviewed)

Title of proceedings 2013 IEEE Sixth International Conference on Cloud Computing (CLOUD'13)
Place Santa Clara, CA, USA
DOI 10.1109/cloud.2013.89

Abstract

Cloud computing is a well known paradigm, featuring on-demand provisioning of virtual machines (VMs) with different sizes and images. Systems deployed in the cloud can thus be heterogeneous, i.e., using multiple different types of VM instances. The immediate performance challenge arises: how to best use heterogeneous VM instances such that the experienced performance, i.e., response times, on different VMs are similar. In this paper, we first show to what extent deployed systems are heterogeneous in clouds by collecting data from operational data centers. We also show that response times suffer from high variance across replicas hosted on different VMs. We develop a novel plug&play workload controller, Join-the-Best-Queue (JBQ), which aims to reduce the variance and higher percentile of response-times in heterogeneous environments. With the aid of a testbed hosting part of wikipedia in an operational cloud, we show that JBQ can significantly reduce performance variability across different VMs, compared to prevailing load distributing policies in the Apache web server.
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