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Posters and Demonstrations at GENI NICE 2017


Steroid Openflow Service

With the recent rise in cloud computing, applications are routinely accessing and interacting with data on remote resources. As data sizes become increasingly large, often combined with their locations being far from the applications, the well known impact of lower TCP throughput over large delay-bandwidth product paths becomes more significant to these applications. A software defined networking based solution called Steroid OpenFlow Service (SOS) is a network service that transparently increases the throughput of data transfers across large networks. In an OpenFlow-based cloud environment such as GENI, SOS can leverage the use of multiple agents to provide increased network throughput for many applications simultaneously. A cloud-based approach is particularly beneficial to applications in environments without access to high performance networks. In the demo we will show SoS running and webUI showing the real time plots of bandwidth utilization.


  • Khayam Anjam, Clemson University

A Behavior-Driven Approach for Expressive Intent Specification in SDN and NFV

One of the goals of Software-Defined Networking (SDN) is to allow users to specify high-level policies into lower level network rules. Managing a network and decide what policies is appropriate requires, however, expertise and low level know-how. An emerging SDN paradigm is to allow higher-level network level decisions wishes in the form of intents"". Despite its importance in simplifying network management, intent specification is not yet standardized.

In this work, we propose an intent declaration approach based on Behavior-Driven Development (BDD). The level of expressiveness of our approach is maximal: intents are specified in plain English, and translated by our system into network policies, that are in turn, converted into low-level rules by the SDN (ryu) controller. Using the GENI testbed, in this work we demonstrate how to use our BDD framework to declare a few representative network intents: access control with a stateless firewall and traffic steering.


  • Flavio Esposito, St. Louis University
  • Thomas Merod, St. Louis University
  • Holly Wang, St. Louis University

Network Protocols

SPAN: Authentication protocol for software defined networking

SPAN is Multiparty Trust Negotiation (MTN) protocol that establishes mutual trust by the exchange of digital credentials and access control policies (ACP) among entities that may have no prior knowledge about each other. Research done in the area of automatic negotiation has been focus on creating an agreement between two parties however real world agreements involve more than two parties. In this paper we extend the stateless Eager Attribute Negotiation (SEAN) algorithm [9] to work in a multiparty environment. The proposed protocol is a distributed protocol and no centralized moderator is required. As a proof of concept we include an example that shows how this algorithm works.


  • Maha Allouzi, Kent State University
  • Javed Khan

Emergency High-Speed Internet Lane Protocol

The objective of emergency response is to minimize the impact of the event over time, particularly human casualties, environmental damage, and community disruption. Robust, reliable, and timely information sharing and dissemination is foundational to successful response. Thus, it is important to pursue information gathering to inform best practice response and rescue. Collecting and sharing the emergency data and information in a timely, reliable and effective manner to decision-makers, including Incident Command (IC) and to the responsible Public Safety Organizations (PSOs) through a regional center is vital to the success of emergency response. Current traffic routing in the Internet is subject to frequent route changes and high churn rates leading to delayed, looping, and lost packets. Lost and delayed packets can be highly detrimental to rescue operations. It is important to handle transportation of emergency information between the IC and Emergency Management Office (EMO)/PSO such that they are minimally impacted by routing instability and delays due to other traffic in the Internet. A new protocol called the Multi Node Label Routing (MNLR) Protocol has been developed to operate transparently to the Internet Protocol, providing a high-speed Internet lane for emergency information. It is designed with an immediate failover mechanism—meaning that if a link or node fails, it uses an alternate path right away, as soon as the failure is detected. The protocol has been implemented in GENI and uses a novel addressing scheme with labels auto assigned to nodes as they join the network. In this demo, we will show the capabilities of MNLR that will allow for auto-configuration of the nodes with multiple labels and the rapid recovery upon failures in the network, using a live video stream as an example application running on the network. The MNLR protocol failure detection and recovery operations will be directly compared with both Open Shortest Path First and Border Gateway Protocol running in their own networks.


  • Nirmala Shenoy, RIT
  • Erik Golen, RIT
  • Supriya Kharade, RIT
  • Shashank Rudroju, RIT

AGRA: AI-augmented geographic routing approach for IoT-based incident-supporting applications

Applications that cater to the needs of disaster incident response generate large amount of data and demand large computational resource access. Such datasets are usually collected in real-time at the incident scenes using different Internet of Things (IoT) devices. Hierarchical clouds, i.e., core and edge clouds, can help these applications’ real-time data orchestration challenges as well as with their IoT operations scalability, reliability and stability by overcoming infrastructure limitations at the ad-hoc wireless network edge. Routing is a crucial infrastructure management orchestration mechanism for such systems. Current geographic routing or greedy forwarding approaches designed for early wireless ad-hoc networks lack efficient solutions for disaster incident-supporting applications, given the high-speed and low-latency data delivery that edge cloud gateways impose. In this demo, we present a novel Artificial Intelligent (AI)-augmented geographic routing approach, that relies on an area knowledge obtained from the satellite imagery (available at the edge cloud) by applying deep learning. In particular, we propose a stateless greedy forwarding that uses such an environment learning to proactively avoid the local minimum problem by diverting traffic with an algorithm that emulates electrostatic repulsive forces. In our theoretical analysis, we show that our Greedy Forwarding achieves in the worst case a 3.291 path stretch approximation bound with respect to the shortest path, without assuming presence of symmetrical links or unit disk graphs. We establish the practicality of our approach in a real incident-supporting hierarchical cloud deployment to demonstrate improvement of application level throughput due to a reduced path stretch under severe node failures and high mobility challenges of disaster response scenarios.


  • Dmitrii Chemodanov, University of Missouri
  • Jon Patman, University of Missouri

Education, Tools

The Popper Experimentation Protocol: Applying DevOps to the Evaluation of Computer Systems

Current approaches to scientific research require time-consuming activities that do not advance our scientific understanding. For example, cleaning data and writing code to attempt to reproduce previously published research. Can we find a better way to create and publish workflows, data, and models? The Popper Experimentation Protocol ( is a series of simple, easy-to-follow steps for implementing experiments using a DevOps approach.

Modern OSS development communities have created tools and practices (DevOps) to manage large codebases, allowing them to deal with high levels of complexity, not only in terms of code, but with the entire ecosystem that is needed in order to deliver changes to software in an agile, rapidly changing environment. Popper repurposes DevOps in the context of scientific explorations.

We will illustrate how to make use of the Popper command-line tool in order to re-run an existing experiment using geni-lib to configure infrastructure. Subsequently, we will show how to make use of Ansible and Docker, as well as to implement post-analysis of results using Jupyter notebooks. Additionally, we will show how Popper can generate files that can be used to connect a GitHub project (a ""Popperized"" repo) with TravisCI to continuously validate experiments.


  • Ivo Jimenez, University of California, Santa Cruz
  • Michael Sevilla
  • Noah Watkins
  • Jay Lofstead
  • Carlos Maltzahn
  • Kathryn Mohror
  • Andrea Arpaci-Dusseau
  • Remzi Arpaci-Dusseau

Virtual Computer Networks Lab

Jupyter is a widely used open-source tool based on the IPython implementation that allows users to share and run code in a browser. We will demonstrate the functionality of Jupyter for network testbed experimentation. We will present classroom assignments that can be instrumented in GENI through Jupyter.


  • Bhushan Suresh, University of Massachusetts at Amherst
  • Divyashri Bhat, University of Massachusetts at Amherst
  • Michael Zink, University of Massachusetts at Amherst