[Colloquium] Reminder: Nguyen/MS Presentation/Jul 9, 2019

[Margaret Jaffey]

Please note the location change for Hai Nguyen's MS Presentation on
Tuesday. It will be held in JCL 298.

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Date:  Tuesday, July 9, 2019

Time:  1:30 PM

Place:  John Crerar Library 298

M.S. Candidate:  Hai Nguyen

M.S. Paper Title: Cloud Resource Management for Bursty, Real-time
Workloads

Abstract:
Today's cloud resource offerings provide no guarantees for resource
allocation, so bursty, real time applications must reserve, and pay
for resources they do not use - to achieve real-time guarantees. We
propose Real-time Serverless, a new type of cloud resource with a new
service-level objective -- guaranteed allocation rate. This guarantee
enables timely resource allocation, enabling applications to achieve
real-time performance efficiently with good resource utilization and
cost. With a simple burst model, we study real-time serverless
analytically, exploring its effect on application quality, guarantees,
and cost. Next, we use simulation to explore a statistical variety of
bursts and higher loads (multi-application), to study the benefits of
Real-time Serverless for applications.

In both analytic and simulation studies, the availability of real-time
serverless service enables bursty, real-time applications to achieve
guaranteed high quality cost-effectively. Specifically, for a desired
application quality, the required allocation rate can be determined.
Real-time serverless also enables applications to match resources to
demands and thereby minimize the cost. For example, for duty factors
from 0.025 to 0.25, the value per unit resource of Real-time
Serverless instances to a bursty application can be 4x higher than
traditional. Further results show the robustness of real-time
serverless with bursty, real-time applications over a wide range of
properties. Multiple applications can share a real-time serverless
pool efficiently, supporting duty factor increases of 25x with only a
1.6x increase in allocation rate (provider resource cost), revealing
high resource management flexibility and economic potential to cloud
providers.

We present a case study of a video-based traffic monitoring
application. Despite more complex burst statistics, our results show
major benefits for application quality and cost. For this application,
real-time serverless instances are worth nearly 16x per unit resource,
when compared to virtual machine resources. Finally, we introduce a
simple implementation of real time serverless to demonstrate its
feasibility and capability to support bursty, real-time workloads
efficiently.

Hai's advisor is Prof. Andrew Chien

Login to the Computer Science Department website for details:
 https://newtraell.cs.uchicago.edu/phd/ms_announcements#ndhai

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Margaret P. Jaffey            margaret at cs.uchicago.edu
Department of Computer Science
Student Support Rep (Ry 156)               (773) 702-6011
The University of Chicago      http://www.cs.uchicago.edu
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