perfSONAR NSF Proposal

We propose to work with the National University of Sciences and Technology (NUST) / Institute of Information Technology1 in Pakistan to collaborate closely with the perfSONAR collaboration to extend the perfSONAR framework2 and deploy it in Pakistan. perfSONAR offers an open source, open community solution to the problem of gathering network performance statistics over a multitide of different administrative domains and technological differences. It is currently being rolled out across both the United States of America (through Internet2 and ES-net) and Europe (Geant2, Surfnet, RedClara, Pioneer etc).

The perfSONAR framework allows hardware transparency in the gathering and storage of data. It also provides the means by which network diagnostic tools3 can be included in the collection of network metrics. It therefore provides a mechanism whereby both the backbone properties and the end-to-end capabilities of the network can be interrogated and the results archived for later analysis.
As such, perfSONAR extends the measuring and sharing of information across a wider range of autonomous domains. Through the use of authentication, authorization and auditing, sensitive information about the network can also be protected. perfSONAR therefore enables network engineers, system administrators and users to dramatically reduce the extraordinary amount of time they utilize today coordinating debugging efforts across multiple domains and in building up flexible, coherent monitoring infrastructures.

In particular the collaboration between NUST and Stanford Linear Accelerator Center (SLAC) will focus their efforts on mining the vast amounts of network data to aid not only the gathering and storage of network performance information, but to develop tools and applications to provide in-depth analysis and reporting, visualization and interactivity, forecasting and automatic event detection, network and application diagnostics and problem solving, network usage characterization for forward planning, and topology discovery at network layers 1 to 4. This will provide an extensive suite of tools that will exploit the potential of the perfSONAR framework.

In addition we wish to deploy the perfSONAR and related tools on the Pakistan Educational and Research Network (PERN). We feel that this is important in order to provide a means by which the network operator can not only be held accountable for the performance of their network, but also provide mechanisms by which their network engineers can better utilize their efforts.
Through the contribution of internal development teams at NUST, whom will work closely with PERN and SLAC, tools built on the perfSONAR framework will place PERN as a major contributor to the National Research and Education Networks (NRENs) and will aid the performance and deployment of network dependent applications such as CERN's Large Hadron Collider (LHC) Network4, telemedicine, etc. etc.

The NUST Institute of Information Technology has been playing its part for more than three years by maturing a collaborative research initiative with SLAC, USA. With expected growth in bandwidths, PERN will also be able to benefit from more advanced tools being developed by SLAC and its collaborators in the US and Europe. The interdisciplinary composition of this proposal encompasses the following: computer networking, software engineering, statistical analysis, high energy physics/science and geopolitics.

[1] NIIT will be funded out of a separate grant from the Pakistan Higher Education Commission (HEC).
[2] The perfSONAR framework is supported by the perfSONAR consortium (http://www.perfsonar.net) recently initiated by the joint collaboration of Internet2, the European Union-funded GEANT2 project, the DoE energy Sciences Network (ESNet), Georgia Institute of Technology (GaTech) and the Stanford Linear Accelerator Center (SLAC). Since NIIT is working in strong collaboration with SLAC, PERN shall be able to benefit from the experience of our collaboration by virtue of PETWORK.
[3] Network diagnostics tools such as OWAMP, NDT, BWCTL (a scheduler for iperf) have proven to be vital for Internet2 to understand the performance trends and in solving network performance problems.
[4] The Pakistan NIIT and National Center for Physics (NCP) sites are both building Grid clusters to provide services for the LHC, and so will need both excellent networking for data distribution, and perfSONAR in Pakistan to diagnose network problems end-to-end.