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What and Who
Title:Automated Resource Management in Large-Scale Networked Systems
Speaker:Sangeetha Abdu Jyothi
coming from:University of Illinois
Speakers Bio: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).


Event Type:SWS Colloquium
Visibility:D1, D2, D3, INET, D4, D5, SWS, RG1, MMCI
We use this to send out email in the morning.
Level:AG Audience
Date, Time and Location
Date:Monday, 11 March 2019
Duration:60 Minutes
Building:E1 5
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.

Name(s):Gretchen Gravelle
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:YesTo Location:Kaiserslautern
To Building:G26To Room:111
Meeting ID:
Tags, Category, Keywords and additional notes
Keywords:Internet applications, Cloud
Attachments, File(s):

Gretchen Gravelle/MPI-SWS, 02/12/2019 09:59 AM
Last modified:
Uwe Brahm/MPII/DE, 03/11/2019 07:01 AM
  • Gretchen Gravelle, 03/06/2019 01:42 PM
  • Gretchen Gravelle, 02/12/2019 10:03 AM -- Created document.