Less can me more: micro-managing VMs in Amazon EC2

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Title: Less can me more: micro-managing VMs in Amazon EC2
Author(s): Wen, J
Lu, L
Casale, G
Smirni, E
Item Type: Conference Paper
Abstract: © 2015 IEEE.Micro instances (t1. micro) are the class of Amazon EC2 virtual machines (VMs) offering the lowest operational costs for applications with short bursts in their CPU requirements. As processing proceeds, EC2 throttles CPU capacity of micro instances in a complex, unpredictable, manner. This paper aims at making micro instances more predictable and efficient to use. First, we present a characterization of EC2 micro instances that evaluates the complex interactions between cost, performance, idleness and CPU throttling. Next, we define adaptive algorithms to manage CPU consumption by learning the workload characteristics at runtime and by injecting idleness to diminish host-level throttling. We show that a gradient-hill strategy leads to favorable results. For CPU bound workloads, we observe that a significant portion of jobs (up to 65%) can have end-to-end times that are even four times shorter than those of the more expensive m1. small class. Our algorithms drastically reduce the long tails of job execution times on the micro instances, resulting to favorable comparisons against even small instances.
Publication Date: 19-Aug-2015
Date of Acceptance: 27-Jun-2015
URI: http://hdl.handle.net/10044/1/32282
DOI: http://dx.doi.org/10.1109/CLOUD.2015.50
ISBN: 9781467372879
Publisher: IEEE
Start Page: 317
End Page: 324
Journal / Book Title: 2015 IEEE 8th International Conference on Cloud Computing
Copyright Statement: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: 2015 IEEE 8th International Conference on Cloud Computing
Publication Status: Published
Start Date: 2015-06-27
Finish Date: 2015-07-02
Conference Place: New York, USA
Appears in Collections:Faculty of Engineering
Computing



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