- About
- Events
- Events
- Calendar
- Graduation Information
- Cornell Learning Machines Seminar
- Student Colloquium
- BOOM
- Spring 2025 Colloquium
- Conway-Walker Lecture Series
- Salton 2024 Lecture Series
- Seminars / Lectures
- Big Red Hacks
- Cornell University / Cornell Tech - High School Programming Workshop and Contest 2025
- Game Design Initiative
- CSMore: The Rising Sophomore Summer Program in Computer Science
- Explore CS Research
- ACSU Research Night
- Cornell Junior Theorists' Workshop 2024
- People
- Courses
- Research
- Undergraduate
- M Eng
- MS
- PhD
- PhD
- Admissions
- Current Students
- Computer Science Graduate Office Hours
- Advising Guide for Research Students
- Business Card Policy
- Cornell Tech
- Curricular Practical Training
- A & B Exam Scheduling Guidelines
- Fellowship Opportunities
- Field of Computer Science Ph.D. Student Handbook
- Graduate TA Handbook
- Field A Exam Summary Form
- Graduate School Forms
- Instructor / TA Application
- Ph.D. Requirements
- Ph.D. Student Financial Support
- Special Committee Selection
- Travel Funding Opportunities
- Travel Reimbursement Guide
- The Outside Minor Requirement
- Robotics Ph. D. prgram
- Diversity and Inclusion
- Graduation Information
- CS Graduate Minor
- Outreach Opportunities
- Parental Accommodation Policy
- Special Masters
- Student Spotlights
- Contact PhD Office
There have been many recent proposals to change the network infrastructure in order to meet different performance objectives. These changes are often difficult to deploy, either requiring specialized network switching hardware or greatly complicating network management. Rather than continuing to add new features to the network in an ad-hoc manner, my work advocates a principled approach for meeting different performance objectives, that leads to a more stable network infrastructure. This approach is based on the following two questions: First, can we avoid making changes to the network infrastructure by looking for solutions that only change the end-points? Second, when infrastructure changes are needed, can we make them universal in nature? In this talk, I will primarily focus on the second question, where I explore whether we can have a universal packet scheduling algorithm, that can mimic all other scheduling algorithms. Towards the end, I will briefly present three examples in the context of wide-area and datacenter congestion control, where I tackle the first question of avoiding changes to the network infrastructure.
Bio:
Radhika Mittal is a Phd candidate in the Computer Science Department at UC Berkeley, where she is advised by Prof. Sylvia Ratnasamy and Prof. Scott Shenker. Her work has covered several topics in computer systems and networking. Before starting at UC Berkeley in 2012, she received her bachelor degree in Computer Science and Engineering from IIT Kharagpur in India.