Changes between Version 4 and Version 5 of GENINICE/EveningDemoSession


Ignore:
Timestamp:
11/04/15 13:36:37 (6 years ago)
Author:
peter.stickney@bbn.com
Comment:

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  • GENINICE/EveningDemoSession

    v4 v5  
    116116 * Zak Zafar
    117117 * Esma Yahia
     118
     119=== SDN & NFV ===
     120
     121==== Network Measurement & Inference with SDN-enabled Online Learning ====
     122
     123Fine 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.
     124
     125Participants:
     126 * Chang Liu, cchliu@ucdavis.edu, University of California-Davis
     127 * Mehdi Malboubi
     128 * Chen-Nee Chuah
     129
     130==== Virtual Network Migration Mechanism on GENI Platform ====
     131
     132Network 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.
     133
     134Participants:
     135 * Yimeng Zhao, zhaoym428@gmail.com
     136 * Samantha Lo
     137 * Niky Riga
     138 * Mostafa Ammar
     139 * Ellen Zegura
     140
     141==== TBD ====
     142
     143My demo is based generally on the openFlow architecture, and more specifically my demo consists of:
     144 * Floodlight
     145 * OVS Swithes(Open vSwitch): precisely I am using 10 of these Switches
     146 * 2 nodes, 1 as the client and the other one is the server.
     147
     148The 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.
     149
     150Then the next step of my research will be improving this algorithm to cover the security part, and how to avoid the communication attacks.
     151
     152Participants:
     153 * Mohamed Rahouti, mrahouti@mail.usf.edu, University of Southern Florida
     154 *  Dr. Kaiqi Xiong
     155