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What and Who

Automated Resource Management in Large-Scale Networked Systems

Sangeetha Abdu Jyothi
University of Illinois
SWS Colloquium

Sangeetha Abdu Jyothi is a Ph.D. candidate at the University of Illinois at Urbana-Champaign. Her research interests lie in the areas of computer networking and systems with a focus on building application-aware self-optimizing systems through automated resource management. She is a winner of the Facebook Graduate Fellowship (2017-2019) and the Mavis Future Faculty Fellowship (2017-2018). She was invited to attend the Rising Stars in EECS workshop at MIT (2018).
Website: http://abdujyo2.web.engr.illinois.edu
AG 1, AG 2, AG 3, INET, AG 4, AG 5, SWS, RG1, MMCI  
AG Audience
English

Date, Time and Location

Monday, 11 March 2019
10:30
60 Minutes
E1 5
029
Saarbrücken

Abstract

Internet applications rely on large-scale networked environments such as the cloud for their backend support. In these multi-tenanted environments, various stakeholders have diverse goals. The objective of the infrastructure provider is to increase revenue by utilizing the resources efficiently. Applications, on the other hand, want to meet their performance requirements at minimal cost. However, estimating the exact amount of resources required to meet the application needs is a difficult task, even for expert users. Easy workarounds employed for tackling this problem, such as resource over-provisioning, negatively impact the goals of the provider, applications, or both.

In this talk, I will discuss the design of application-aware self-optimizing systems through automated resource management that helps meet the varied goals of the provider and applications in large-scale networked environments. The key steps in closed-loop resource management include learning of application resource needs, efficient scheduling of resources, and adaptation to variations in real time. I will describe how I apply this high-level approach in two distinct environments using (a) Morpheus in enterprise clusters, and (b) Patronus in cellular provider networks with geo-distributed micro data centers. I will also touch upon my related work in application-specific context at the intersection of network scheduling and deep learning. I will conclude with my vision for self-optimizing systems including fully automated clouds and an elastic geo-distributed platform for thousands of micro data centers.

Contact

Gretchen Gravelle
068193039102
--email hidden

Video Broadcast

Yes
Kaiserslautern
G26
111
passcode not visible
logged in users only

Tags, Category, Keywords and additional notes

Internet applications, Cloud

Gretchen Gravelle, 03/06/2019 13:42
Gretchen Gravelle, 02/12/2019 10:03 -- Created document.