GENI Webinar Series - July 15 - Virtual Computer Networks Lab

[Ben Newton]

Join us on Friday July 15 at 11:00 a.m. ET for the next in our series of GENI Webinars.  This month Michael Zink from the University of Massachusetts Amherst will present::

Virtual Computer Networks Lab

In this webinar we will present a series of course modules, which we have developed as part of our GENI Virtual Computer Networks Lab. These course modules have been designed with a focus on undergraduate education in computer networking and distributed system. They can be used by educators as classroom assignments. In addition, they can be used by experimenters as tutorials to learn how to use GENI testbeds and how to execute experiments on such testbeds. We will demonstrate the tools and mechanisms that have been integrated in the modules to support such assignments.

In this webinar, we will introduce four of our course modules and lead the audience through one of the modules step by step. This will give the audience an overview on the capability of our modules and how GENI testbeds can be used in education.

To receive connection information, and updates on this and other webinars in the series, please fill out and submit the form below, or fill it out here.

Also, click here for the full webinar schedule and more info.

Thanks,

  Ben Newton, Jay Aikat, and Kevin Jeffay (University of North Carolina at Chapel Hill)

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[Ben Newton]

Join us on Friday August 26th at 3:00 p.m. ET for the next in our series of GENI Webinars.  This month Paul Ruth from the Renaissance Computing Institute (RENCI):

Distributed Computing on GENI: Hadoop in a Slice

GENI is an excellent tool for experimenting with distributed computing. Hadoop is a popular framework for storing and processing large distributed datasets. This webinar uses Hadoop to demonstrate how to deploy scalable distributed applications across the GENI infrastructure.

The webinar walks participants through creating a Hadoop slice composed of three virtual machines that are a Hadoop cluster. The tutorial will lead you through creating the slice, observing the properties of the slice, and running a Hadoop example that sorts a large dataset. Upon completion of the exercise, participants will be able to experiment with scaling the Hadoop sorting application and should be able to apply their new skill to deploy other distributed applications.