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GENI NICE Evening Demos


Sheraton Fisherman's Wharf Hotel
2500 Mason St
San Francisco, CA 94133


Tuesday Nov 10, 2015 - 5.30pm - 7.30pm

Session Leaders

Manu Gosain
GENI Project Office
Peter Stickney
GENI Project Office


The evening demo session gives GENI NICE experimenters and developers a chance to share their work in a live network environment. Demonstrations run for the entire length of the session, with teams on hand to answer questions and collaborate. This page lists requested demonstrations categorized in broad interest groups. You can download project posters and supplemental information from attachments listed at the bottom of this page.



Virtual Computer Networks Lab

Attendees interested in using GENI for education should attend this demo. In this demo we will present assignments that we have created within the scope of our GENI Virtual Computer Networks Lab. These assignments are executed on GENI testbeds and can be used by teachers in their Computer Networks or Distributed Systems classes. In addition to the assignments we will demonstrate LabWiki and how it can be used by students to execute the assignments. We will also demonstrate LabWiki’s features that support teachers in setting up and evaluating assignments.


Education Modules using GENI

This is a demo (with a poster at the demo station as well) of education modules that can be used in undergraduate networking classes. We have developed several curricular modules to teach basic networking concepts, including congestion control, TCP vs UDP, exploring router size, and several others.

If you teach networking courses, and would like toteands-on real demo, in-class tutorials, or assignments using GENI infrastructure to reinforce concepts through experimentation, please stop by our demo, and visit:


  • Jay Aikat,, The University of North Carolina at Chapel Hill
  • Kevin Jeffay
  • Ryan Doyle

Future Internet Architectures

Load Balancing Approach for Adaptive Bit-Rate Streaming in Information Centric Networks

The Information Centric Networking (ICN) paradigm promises deconstraining the current Internet architecture by allowing clients to directly address the desired content throughout the network. For the Internet, this is an evolutionary step from the idea of a narrow-waist core that only transports requests/replies to an intelligent architecture searching for and providing content. Multi-sourcing, which is one of the core ideas of ICN, constitutes a serious challenge for prevalent Internet applications such as video streaming. In this work we show how prominent adaptive video streaming protocols can benefit from the load balancing capabilities that are native to ICN. We examine the performance of content retrieval in ICN over Ethernet in a real-world testbed showing the impact of multi-sourcing and content size variation on the content transfer times.


Efficient Caching for Dash

Dynamic Adaptive Streaming over HTTP (DASH) is a recent technology that delivers high quality streaming media content over the Internet using HTTP servers. A DASH server contains multiple representations for every video, with each representation varying in bitrate, resolution etc. Each of these representations are divided into smaller segments of fixed playback duration. the client downloads the individual segments during playback. The client employs an Adaptive Bitrate Algorithm (ABR) that determines the appropriate quality for the next segment based on the network conditions. The current Internet architecture utilizes in-network caching to improve content availability and performance. We identify the areas where DASH differs from other web requests, and propose an Adaptation Aware Cache (AAC) framework that optimizes serving DASH video streams by using bandwidth measurement at the cache and the knowledge of the adaptation scheme used at the client to predict the next segment request. This technique could be used to improve the cache performance by maximizing the byte-hits in cache and minimizing the unnecessary prefetches, thus improving the Quality of Experience (QoE) at the client-end.

To evaluate our proposal we used GENI testbed a web-server that host multiple DASH videos with several representations. All the segment request from the client are serviced using a single machine acting as a cache. The cache measures the current bandwidth based on one of the three throughput estimations: average of all values, average of last five values, and Harmonic average of all values.


  • Sheyda Kiani Mehr,, University of Missouri-Kansas City
  • Parikshit Juluri
  • Rohit Abhishek
  • Deep Medhi

Network Protocols

A Flexible and Lightweight BGP Route Injector to Multiple Peers

The demo proposes and implements a flexible and lightweight BGP injector (mBGPInjector) that can announce both offline and real-time BGP routes to multiple peers with various filtering options. mBGPInjector also supports dynamical BGP configuration changes, such as online bringing a peer down or up, applying custom filtering rules and announcing or withdrawing arbitrary BGP routes. The implemented mBGPInjector is a lightweight perl program that consists of a few functions to read, analyze and direct BGP routes to corresponding connected BGP peers in a large size of network (eBGP or iBGP). Experiments with our mBGPInjector tool satisfy the requirements we need for research and education and demonstrate effectiveness under realistic workloads. In addition, we designed and tested the tool in Global Environment for Network Innovations (GENI) environment, where researchers and educators can take advantage of shared resource request files to repeat the same experiments without involvement of ponderous settings and configurations.


WiFi Multicast to Very Large Groups - Experimentation on the ORBIT Testbed

While WiFi has been proposed for multimedia content distribution, its lack of adequate support for multicast services hinders its ability to provide multimedia content distribution to a large number of devices. In our recent papers we proposed AMuSe, a scalable and adaptive system for WiFi multicast which is based on accurate receiver feedback and that incurs a small control overhead. Specifically, the system includes a scheme for dynamic selection of a subset of the multicast receivers as feedback nodes, which periodically send information, such as channel quality or received packet statistics, to the multicast sender.We implemented the AMuSe system in the ORBIT testbed and evaluated its performance in large groups with 150-200 receivers. We present a dynamic web-based application that demonstrates the operation of the system based on actual traces collected on the testbed in several experiments. It demonstrates the operation of AMuSe in various setting and environments.


  • Varun Gupta,, Columbia University
  • Raphael Norwitz
  • Savvas Petridis
  • Craig Gutterman
  • Gil Zussman
  • Yigal Bejerano

Next Generation Applications

A Cyber Physical Test Bed for Advanced Manufacturing

This demonstration will be a milestone in the area of Digital Manufacturing and involves showcasing a GENI based cyber physical framework for advanced manufacturing. This Next Internet based framework will enable globally distributed software and manufacturing resources to be accessed from different locations accomplish a complex set of life cycle activities including design analysis, assembly planning, and simulation. The advent of the Next Internet holds the promise of ushering in a new era in Information Centric engineering and digital manufacturing activities. The focus will be on the emerging domain of micro devices assembly, which involves the assembly of micron sized parts using automated micro assembly work cells.



Network Measurement & Inference with SDN-enabled Online Learning

Fine grained information about the Internal Attributes of Interest (IAI) of a network, such as the per-flow size, delay, throughput or packet loss, provides an essential input for network design, capacity planning, routing protocol configuration and anomaly detection. In this poster, we would like to revisit the problem of network inference in the context of SDN-based networks. Using traffic matrix estimation (TME) as a case study, we propose a new measurement & inference framework with SDN-enabled online learning and show the performance of our framework for TM estimation and (hierarchical) heavy-hitter detection.


Virtual Network Migration Mechanism on GENI Platform

Network virtualization provides flexibility, enables agility and increases manageability by allowing coexistence of multiple virtual networks on the same physical substrate. Virtual network is built on top of the physical infrastructure and is assigned a subset of the underlying physical network resources. To have a better resource management, to recover from failure or provide defense against attacks, virtual networks may need to be remapped to different physical locations from time to time. However, there has not been a lot of work addressing the challenges of deploying a virtual migration mechanism in real infrastructure and exploring how the interaction between the virtual network and substrate network can affect the desired migration. In our project, we design and evaluate a virtual network migration mechanism in Openflow-enabled GENI platform. Specifically, we want to explore (1) how to deploy virtual network on GENI platform, (2) how to design a migration controller to make migration quick and automatic, and (3) how to minimize the disruption caused by migration. We will reveal the challenge and restriction to conduct virtual network migration experiments on GENI, and give recommendations for GENI platform to enhance their ability to support virtual network migration experiments.



My demo is based generally on the openFlow architecture, and more specifically my demo consists of:

  • Floodlight
  • OVS Swithes(Open vSwitch): precisely I am using 10 of these Switches
  • 2 nodes, 1 as the client and the other one is the server.

The purpose of my research is finding the best algorithm that guaranties the fastest communication between the client and the server node when n numbers of OVS Swithes are being interconnected to the client and the server host.

Then the next step of my research will be improving this algorithm to cover the security part, and how to avoid the communication attacks.