Changes between Version 16 and Version 17 of netKarma/GEC13_report


Ignore:
Timestamp:
03/21/12 21:36:00 (12 years ago)
Author:
scjensen@umail.iu.edu
Comment:

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  • netKarma/GEC13_report

    v16 v17  
    1212For the quarter ending with GEC13, we released the NetKarma portal which allows experimentors to easily add and retrieve experimental data from the NetKarma provenance archive. The NetKarma Portal is integrated with the NetKarma Provenance System and provides a persistent service on servers at Indiana University to enable GENI experimentors to help understand the conditions of their experiment. The NetKarma links the experiment workflow data obtained from tools such as GUSH to representations of the experiment's GENI topology, the GENI Instramentation and Measurement systems, and log term data archives. NetKarma links all of these systems together to simplify the complexity of running an experiment on the GENI framework.
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    14 In the plan for evaluating NetKarma we had identified experiments being performed in GENI by researchers at Clemson University on distributed denial of service (DDoS) attacks in WiMAX as a means to evaluate the provenance being captured by Karma.  Since GEC12 we have implemented their experiment, and using the standard trace log that is generated and an extension we added to capture the experiment topology, we are able to harvest detailed provenance about their experiment.  The DDoS experiments measure the change in throughput as a set of network parameters are varied, resulting in over 700 different configurations being tested.  Using the provenance captured from the logs for each packet that was successfully transferred, and the inferred provenance of packets that were dropped, the NetKarma visualization plug-ins can be used to visualize the throughput and packets dropped as shown in Figure __ below.  In addition, the NetKarma visualization plug-n for Cytoscape enables researchers to view the provenance at different levels of granularity as shown in Figure __.  We shared the visualization plugin and provenance graphs generated with the researchers at Clemson and they noted that NetKarma allows them to visualize and compare individual runs whereas previously their analysis was based on ANOVA calculations at an aggregate level.  At GEC13 we presented a demo that visualized the provenance based on our runs of Clemson's experiment to show how provenance can be used to visualize results and is valuable for communicating the results of GENI experiments to other researchers.
     14In the plan for evaluating NetKarma we had identified experiments being performed in GENI by researchers at Clemson University on distributed denial of service (DDoS) attacks in WiMAX as a means to evaluate the provenance being captured by Karma.  Since GEC12 we have implemented their experiment, and using the standard trace log that is generated and an extension we added to capture the experiment topology, we are able to harvest detailed provenance about their experiment.  The DDoS experiments measure the change in throughput as a set of network parameters are varied, resulting in over 700 different configurations being tested.  Using the provenance captured from the logs for each packet that was successfully transferred, and the inferred provenance of packets that were dropped, the NetKarma visualization plug-in can be used to visualize the throughput and packets dropped and view the provenance at different levels of granularity as shown in our demo and poster at GEC13.  We shared the visualization plugin and provenance graphs generated with the researchers at Clemson and they noted that NetKarma allows them to visualize and compare individual runs whereas previously their analysis was based on ANOVA calculations at an aggregate level.  At GEC13 we presented a demo that visualized the provenance based on our runs of Clemson's experiment to show how provenance can be used to visualize results and is valuable for communicating the results of GENI experiments to other researchers.
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    6767__NetKarma Evaluation Based on WiMAX and Provenance Capture/Visualization Enhancements__
    68 Using the WiMAX DDoS attack research from Clemson as a GENI experiment as a basis for evaluation of provenance capture and visualization using NetKarma, we have rerun selected configurations from their research that varied the parameters identified as most significant based on their research while keeping the other parameters constant.  Since their experiments utilized the NS2 simulator, we developed a NetKarma adaptor that can ingest provenance based on NS2 trace logs and an NS2 extension we have made available to capture the network topology.  This new adaptor can be used with other NS2 experiments to ingest provenance into NetKarma (and is not specific to the Clemson experiments).  The adaptor and documentation are available on the NetKarma wiki.  To visualize the provenance of packet transfers (and infer packets dropped) in NS2 experiments, the NetKarma visualization plug-in for Cytoscape was extended with new NS2 visualization algorithms and along with updated documentation is available on the NetKarma wiki as version 1.2.1 of the visualization plug-in.
     68Using the WiMAX DDoS attack research from Clemson as a GENI experiment as a basis for evaluation of provenance capture and visualization using NetKarma, we have rerun selected configurations from their research that varied the parameters identified as most significant based on their research while keeping the other parameters constant.  Since their experiments utilized the NS2 simulator, we developed a NetKarma adaptor that can ingest provenance based on NS2 trace logs and an NS2 extension we have made available to capture the network topology.  This new adaptor can be used with other NS2 experiments to ingest provenance into NetKarma (and is not specific to the Clemson experiments).  The adaptor and documentation are available on the NetKarma wiki.  To visualize the provenance of packet transfers (and infer packets dropped) in NS2 experiments, the NetKarma visualization plug-in for Cytoscape was extended with new NS2 visualization algorithms and along with updated documentation is available on the NetKarma wiki as version 1.2.1 of the visualization plug-in.  The visualization plug-in enhancements allow the packet transfers to be viewed at different levels of granularity as illustrated in the demo and [http://groups.geni.net/geni/attachment/wiki/netKarma/GEC%2013-Role%20of%20Provenance%20in%20Visualizing%20Packet%20Throughput%20and%20Packet%20Loss.pdf poster] we presented at GEC13.
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