| | 57 | ==== GENI for the Masses: Demo of GENI MOOC Project ==== |
| | 58 | |
| | 59 | We will demo an experiment-based Massive Open Online Course (MOOC) on the subject of computer networks, with lab experiments that run on GENI resources. This course is aimed at beginners who want to learn about how the Internet works, students who want an introduction to some research topics in networking, and instructors who may use these browser-based experiments as in-class demonstrations or homework assignments. The first course module, on computer routing, opens at the end of October; interested participants should stop by to see the demo and learn how to register. We will also show a poster on our WiMAX-based lab experiments, which may be of interest to instructors. |
| | 60 | |
| | 61 | Participants: |
| | 62 | * Fraida Fund, ffund@nyu.edu, NYU Polytechnic School of Engineering |
| | 63 | |
| | 64 | Participants: |
| | 65 | |
| | 66 | ==== Size-based Flow Management Enabling Dynamic DMZ ==== |
| | 67 | |
| | 68 | Problem description: The current networking solutions for cybersecurity adopt static policies. Packets from and to supercomputers go through a DPI (deep packet inspection) device for security inspection before being routed toward their destinations. In a network configuration where the bandwidth of the links is equal to 10 gbps and the speed of the DPI is equal to 3 gbps, this device throughput represents the system bottleneck, bringing the bandwidth of the path down to 3 gbps. The adoption of an OpenFlow router allows us to adapt the cybersecurity policies, by dynamically managing the flow forwarding rules. We divide the flows generated by the supercomputers into two groups based on flow sizes: one group consists of elephant flows (the flow size is larger than a threshold) and the other group contains mice flows (the flow size is smaller than a threshold.) The goals of our dynamic flow management are to achieve higher network performance and to gain higher utilization of the network security mechanism. Demo: The client sends multiple flows to the server. The flows are forwarded by a software switch (OpenFlow switch) to the DPI first. Flows sent to the DPI are inspected for network security purposes. When the software switch detects a legitimate elephant flow, the elephant flow will be forwarded directly to the server bypassing the DPI. In this case, we avoid sending the elephant flow through the network bottleneck of the DPI to achieve higher network performance. By our dynamic flow management, we are able to monitor how the multiple flow entries are set up in the software switch flow table and how the flows are rerouted in the network. Equipment: software switch (OpenVSwitch on Ubuntu), Server (iperf on Windows 7), Client (iperf on Windows 7), DPI(OpenVSwitch on Ubuntu), OpenFlow controller(POX on Ubuntu). |
| | 69 | |
| | 70 | Participants: |
| | 71 | * Xin Li, xinli1125@ksu.edu, Kansas State Univ. |
| | 72 | * Haotian Wu, haotianwu@ksu.edu, Kansas State Univ. |
| | 73 | |
| | 74 | ==== PrimoGENI Constellation for Hybrid Network Experimentation ==== |
| | 75 | |
| | 76 | PrimoGENI Constellation allows conducting hybrid, distributed, and at-scale network experiments on GENI resources, combining physical, simulated, and emulated networks. This demonstration will showcase new PrimoGENI capabilities for network researchers to conduct network experiments on various GENI resources, including InstaGENI and ExoGENI racks. This demonstration will also present the new prototype for a public model repository through which experimenters can create, reuse, extend, and share models for network experiments using PrimoGENI. |
| | 77 | |
| | 78 | Participants: |
| | 79 | * liux@cis.fiu.edu, Florida International Univ |
| | 80 | * Mohammad Abu Obaida, mobai001@fiu.edu, Florida International Univ |
| | 81 | * Musa Ahmed, mahme012@fiu.edu, Florida International Univ |
| | 82 | |
| | 83 | ==== Software Switch Data Plane Performance Characterization ==== |
| | 84 | |
| | 85 | The demo is on research with the data plane acceleration methods and their testing methods for software switches. Test planning with OpenFlow-capable software switches has various challenges. The control plane issues may hinder some of the test cases as they have been practiced for non-OpenFlow switches. We investigate solutions to such challenges and report on mapping of test plans on software switch performance characterization. Since most experimental setups utilize software switches for SDN experiments, the results will be applicable to all such SDN application research. |
| | 86 | |
| | 87 | Participants: |
| | 88 | * Deniz Gurkan, dgurkan@central.uh.edu, Univ. of Houston |
| | 89 | * Kyle Longtran, kyle.longtran@gmail.com, Univ. of Houston |
| | 90 | |
| | 91 | ==== Network Complexity Index ==== |
| | 92 | |
| | 93 | We investigate how network complexity index may help determine load balancing and performance guarantee issues in content delivery networks. A content request and response may yield a complexity understanding of the network that is very different from how network nodes are physically connected to each other. Such a representation may lead to better optimizations on the content reachability with load balancing guarantees. The experiment setup will help investigate feasibility of such insight into content delivery networks. |
| | 94 | |
| | 95 | Participants: |
| | 96 | * Deniz Gurkan, dgurkan@central.uh.edu, Univ. of Houston |
| | 97 | * Satyajeet M. Padmanabhi, smpadmanabhi@gmail.com, Univ. of Houston |
| | 98 | |
| | 99 | ==== Hadoop Network Overhead Characterization ==== |
| | 100 | |
| | 101 | The demo is on experimental investigations of overhead in hadoop's network usage while ensuring resiliency in the application layer. We investigate the coordination information exchange in hadoop's typical processing. We report on how such overhead changes with process characteristics and how failures may increase such exchange traffic. A measurement setup on GENI is used to conduct this research. |
| | 102 | |
| | 103 | Participants: |
| | 104 | * Deniz Gurkan, dgurkan@central.uh.edu, Univ. of Houston |
| | 105 | * Abdul Navaz, navaz.enc@gmail.com, Univ. of Houston |
| | 106 | |
