Chameleon on the Networking Channel

Tune in October 27 at 8a PST on the networking channel to hear Chameleon Lead PI Kate Keahey and DevOps lead Jason Anderson speak about how to use Chameleon to run experiments spanning edge devices and the cloud! Learn more: https://bit.ly/3zLoK3Z 

A Statistics-Based Performance Testing Methodology for Cloud Applications

University of Texas, San Antonio Professor Wei Wang and PhD student Sen He investigate performance testing for cloud computing research to help make your research more efficient and cost effective. Learn about their research, which won the ACM SIGSOFT Distinguished Paper award in 2019, experience on Chameleon and AWS, and life philosophies.

Chameleon Changelog for August 2021

In this month's changelog, we announce support for "restricted" edge devices, allowing your research group to temporarily lock down a contributed edge device to only be reservable by your group, but also some more support for interesting peripherals like a camera connected to a Jetson Nano. For more details, come in!

Chameleon@Edge Community Workshop

Date: September 9, 2021

Location: The workshop will take place online, registered attendees will receive details closer to the event date.

Registration: The registration is free and the workshop is open to all, but please bear in mind that registration will close on August 31st. Register at:  https://forms.gle/VmbaCquWMNXe7bCs6

For more details, the call for participation, and agenda, please refer to the announcements page!

Chameleon for Education: IIT’s Intro to Parallel Programming

Interested in using Chameleon for education? Illinois Institute of Technology’s TA and PhD candidate Melanie Cornelius and Dr. Zhiling Lan use Chameleon for undergraduate and graduate students in their Intro to Parallel Programming and Parallel and Distributed Processing classes. Learn all about how the course is structured, incorporating Chameleon into assignments, and tips for using Chameleon for education.

Using Paramiko to Tune Network Performance

Interested in large-scale networking research? Learn more about GENI-style stitching and how to optimize host tuning for 20x performance increases with Python's paramiko package. This blog complements a fully packaged experiment on Trovi, so you can practice doing this yourself! New to Trovi? This blog also outlines how to start running the notebook on Trovi.

Chameleon Hackathon 2021 -- Experiments Reproducibility and Packagability

Call For Participations

The Chameleon team is excited to hold our first Chameleon Hackathon event sometime in the 4th week of August or 1st week of September.  This year’s hackathon will focus on reproducing and packaging experiments on the Chameleon platform.  In this Call for Participations, we would like to survey Chameleon users who are interested in joining this hackathon. Please continue reading and fill out the Google form at the very end.

Chameleon Changelog for July 2021

In this month's changelog, we announce more cool CHI@Edge features, notably support for accessing and reading attached camera data (and other peripherals!). We've also added support for more types of edge devices as we continue to build out the platform. On the bare metal cloud side of things, we've been making improvements to our interfaces--enjoy a refresh of the lease create GUI, which should support more complex types of leases! We also squashed some pesky bugs in the Python API to make it even easier to use Chameleon via Jupyter.

Reproducibility on Chameleon: Trovi meets YouTube

Explore experiments packaged and runnable on Chameleon with ~5 minute videos by the authors explaining how to launch the notebook, provision resources, and run the experiment. Whether you’re new to Chameleon, Jupyter, or Trovi, these videos can help you get started quickly and easily!

Network Traffic Fingerprinting of IoT Devices

This blog features Stevens Institute of Technology PhD candidate Batyr Charyyev’s research on using network traffic fingerprinting of IoT devices for device identification, anomaly detection and user interaction identification. Learn more about Charyyev and his research, including its applications to infer voice commands to smart home speakers.