PAKISTAN-US SCIENCE AND TECHNOLOGY
COOPERATIVE PROGRAM 2007
JOINT PROJECT PROPOSAL

Please provide the required information briefly. Condensed statements are preferred. However, the boxes in
Section 3 may be expanded as necessary. The maximum limit of the project document is 10 pages.

Please do not forget to attach the one-page curricula vitae of all the participating scientists.
Project title:
Measurement and Analysis for the Global-grid and PERN’s
Internet end-to-end Performance (MAGPIE)
Field and subfield of proposed project
Internet Communications: Network Performance Measurement and Analysis
Duration: 3 Years
Starting date: January 2008
PAKISTAN SIDE
Principal Investigator: Prof. Dr. Arshad Ali
NUST Institution of Information Technology
Date
Signature
Address
166A, Street 9 Chaklala Scheme III
Rawalpindi Pakistan 46000
Telephone
92-519280433
Fax
92-519280782
E-mail
arshad.ali@niit.edu.pk
Head of Institution/Vice-Chancellor/Rector
Lt. General (R) Syed Shujaat Hussain, Rector,
National University of Sciences and Technology
Tamiz-Ud-Din Road, PO BOX 297
Rawalpindi, Pakistan
Email: rector@nust.edu.pk
Phone: +92-51-9271575, +92-51-9271576
FAX : +92-51-9271577
US SIDE
Date
Principal Investigator: Dr. Les Cottrell
Stanford University/SLAC
Signature
Address
Stanford University/Stanford Linear Accelerator Center
2575 Sand Hill Road, MS 96
Menlo Park, CA 94025
Telephone Fax
E-mail
(650)
(650)
cottrell@slac.stanford.edu
926-2523
926-3329
Head of Institution/Vice-Chancellor/Rector
c/o Meredith O’Connor,
Managing Senior Contract and Grants Officer
Stanford University
Office of Sponsored Research
320 Panama Street
Stanford, CA 94305
e-mail: meredith.oconnor@stanford.edu
1
2. Project Summary
Title of the Project:
Measurement and Analysis for the Global-grid and PERN’s
Internet end-to-end Performance (MAGPIE)
Pakistan Side
U.S Side
Co-Director: Prof. Dr. Arshad Ali
Co-Director: Dr. Johnathan Dorfan
Institution: NUST Institution of Information
Institution: Stanford University/Stanford Linear
Technology (NIIT)
Accelerator Center (SLAC)
The growth of the Internet has fostered intellectual and economic growth of both developed and
developing countries [i]. Fundamental to this is the operation and maintenance of the underlying Internet
technologies to keep the network functioning and performant.
Specifically, advancements in network connectivity have improved scientists’ ability to collaborate
and helped accelerate the rate of scientific discovery, see for example [ii]. Modern science relies on the
global Internet to create large and physically distributed scientific work environments. Thus scientists
have become more dependent on networking, and network problems have increasing significance. The
pursuit of modern science is thus dependent upon cyber-infrastructure designed to support the efficient
diagnosis of network issues along end-to-end paths traversing multiple networks.
We outline a proposal to enable Pakistan’s advanced education and research facilities to better
understand and utilize their network connections and for Pakistan’s Education and Research Network
(PERN) to become a world leading National Research and Education Network (NREN). Viewing case
studies such as [iii] it is apparent that by monitoring the network, even for Pakistan alone, one can
identify the fragility of computer networks; the problematic routing of traffic e.g. between sites in
Islamabad and Rawalpindi going via London; and despite well provisioned backbones, last mile
problems causing heavy congestion and hence back end-user experience of the Internet.
Understanding network performance can also pose challenges for distributed collaborators.
Scientific communities usually span many physical organizations. The distributed nature of these
communities makes it difficult for campus network engineers or end-users to effectively find or fix endto-end performance problems. Campus networks are usually interconnected via regional networks and
national backbones and may span many domains. Each of these domains usually maintains explicit
control over who can access information and infrastructure and what performance data is shared, if any.
Often, considerable time and effort must be expended to convince physical organizations to begin
testing and it can still be a difficult task to isolate the issue, and even more time can be spent evaluating
different solutions. It is therefore difficult to perform tuning and troubleshooting in distributed
environments due to the need to access information from many different sources and the human
coordination required.
Hence, it is critical that any solution to the problem of network performance monitoring and
diagnostics must be scalable and universal to enable investigators to easily gather network performance
data. More importantly, the framework for this should be capable of conducting automatic analysis,
diagnosis and reporting of network problems for different types of users (e.g. end-users, backbone
administrators etc.).
SLAC, Internet2, ESnet, GEANT, University of Delaware, Georgia Tech and RNP (Brazil) have
begun a global project to deploy such monitoring infrastructures under the perfSONAR framework [iv].
We propose a collaborative effort between SLAC/US and NIIT/Pakistan to help further develop the
various tools and components that will facilitate perfSONAR and apply these tools to the new PERN
network including major end-sites. We intend to help build core services and infrastructure to facilitate
the continued global support of perfSONAR and enable successful scientific collaborations between
Pakistani scientists and their peers worldwide.
We will also tutor and supervise students at NIIT and offer select graduates the opportunity to work
in the US, where they will gain knowledge of research and development in the domain of network
performance monitoring as well as valuable experiences of working at a world class leading research
institute, contacts and best practices in many fields, that they will take back to Pakistan.
2
3. Project Description
3(a) Background and Rationale
To efficiently manage any network one needs to be able to measure it. This includes measuring and
understanding current and long-term performance, identifying and reporting problems both end-to-end
and within the network itself, and providing forecasts of both long and near term performance. Without
such information network managers lack planning information, users and network administrators do not
know what to expect; problems are reported by users, and network administrators spend all their time
fire-fighting; locations and sizes of bottlenecks and their behavior are unknown; and users and
applications are unable to dynamically optimize their network usage.
The extent of ensuring that the network ‘works’ is demonstrated by the fact that network
researchers and end-users have always had a need for network measurement, monitoring, and analysis
tools. This need dates back to the early days of the Internet when the “ping” command was written.
While tools like the ubiquitous “ping” and “traceroute” commands will continue to be the front-line
tools used by most network engineers, more sophisticated tools are needed to directly measure one way
delays, throughput and bandwidth, utilization, non layer 3 paths, etc. Network monitoring tools and
how they are used should answer both basic connectivity type questions and more complex “what’s
wrong with this path” type questions.
Previous efforts to develop these new tools can be sorted into two major classes: (1) individual
tools that can be installed on Internet hosts, (2) measurement tools deployed in a single test domain.
The first class of projects deals with the development of individual measurement tools. These refer
to two types of measurement tools: passive and active. Passive tools (e.g., tcpdump [v], OCx-mon [vi],
Netflow [vii], and Web100 [viii]) make use of application-generated data packets that flow through the
network. A copy of the data packet is passed to the tool for some type of processing. Each tool typically
generates its own unique output format. As with active tools (described below), the output of the tool is
usually handed over to a tool expert for interpretation and analysis. Active tools (e.g., Iperf [ ix], Thrulay
[x], NDT [xi], NPAD [xii]) use a client/server model to generate test packets. The major advantage of
these tools is that individuals and small communities can download and install the tools on an as
needed basis. This ensures that tools are used in a wide variety of operating environments, much larger
than the developers could have achieved. A major disadvantage is that these tools may not be already
installed when problems are reported. Another deterrent is that remote administrators may be reluctant
to install them when they are not sure how the tool works or what its reporting capabilities are. Finally,
tools that require manual action at both ends usually require coordination between remote
administrators and an implicit trust relationship, reducing ease of use.
The second class of projects deploy network-only measurement or monitoring tools inside some
test domain. In addition to individual tools, larger research projects (such as AMP [xiii], Surveyor [xiv],
IEPM-BW [xv], PingER [xvi], RIPE’s Test Project [xvii]) have been established to generate large-scale
measurement and monitoring programs. These projects tend to use both active and passive test tools to
perform their measurement and monitoring functions. A major disadvantage to such systems developed
in such projects is that they have lacked community involvement in the design and are ultimately
limited by the ability of the research team to support such an infrastructure. As a direct result, such
complete systems are hard for non-project members to extend as they have lacked community
involvement in their design. Experience has shown that such projects (see for example AMP and
Surveyor) fade away as funding shifts and people move on to new projects, and those subsequent
projects rarely build on what has come before.
Therefore, a single, monolithic, global measurement system is unrealistic. Federation and neutral
information exchange standards-based formats and a modular mix-and-match architecture are
necessary. This preserves local autonomy while promoting global utility. Moreover, reports and unified
access to the measurement results are needed to provide useful analysis and diagnostics in order to
identify, diagnose and help resolve network performance and connectivity problems to ensure that users
can view the network as a reliable, predictable utility.
3
3(b) Problem Statement
The next generation of the PERN backbone, PERN2 [xviii], will soon be deployed to interconnect
over 60 universities across Pakistan and to the rest of the world. It will offer immense possibilities for
the various network users across diverse disciplines/endeavors such as medical research [xix] [xx,
particle physics [xxi], agro-informatics [xxii], media-communications [xxiii] [xxiv] and distance learning
[xxv].
Figure 1 shows the historical connectivity of the existing international link between SLAC and
NIIT. As the figure shows, network users typically experience very poor performance (RTTs > 250ms
and very variable and heavy losses) and network fragility (100% loss) that makes collaborative
technologies such as video conferencing technically unfeasible at least until late 2006 when
performance improved. As PERN2 is deployed, it is important to not only understand but also to
monitor the network infrastructure and the end-to-end performance to ensure that the return on
investment of such a large project is understood and that network users are able to utilize such
infrastructures.
Figure 1: PingER RTT (blue) in msec. and loss (green) % since May ‘05 thru May ‘07 measured from SLAC to NIIT
To understand the problems of network performance and monitoring, and their effect on network
users, the research community and the local industry, it is beneficial to note how these groups typically
deal with network performance measurement and monitoring issues these days.
Consider two scholars from different universities (but connected by the PERN network) arranging
a video conference to facilitate their collaboration. Hypothetically, when they setup the call, one
scholar finds that the video stream is poor. The scholar then contacts his/her local network
administrator seeking help in resolving the matter. After some preliminary tests the network
administrator suspects that the reason for the poor video quality is insufficient available bandwidth. For
this reason he/she plans to use the Iperf tool to test the links. However, in order to use Iperf there is a
requirement of a server component. Consequently, after hours or possibly days of telephone tag and
coordination with network administrators within each administrative domain, the tests are conducted
and a single link identified behaving as the bottleneck. Later the network administrators corroborate to
fix the problem and scholars are informed that the link would be available after the repair has been
made. This is all with the assumption that the network administrators within each administrative
domain forming the link were available and willing to support the tests. Thus in such scenarios it is safe
to say that days of effort from multiple network administrators is required to first identify the problem,
and later fix it.
Reducing the hours and number of participants required to find and report these types of problems
is a major goal of this proposal. Not only is the time to repair reduced, but the frustration level of the
scientist is also reduced. Knowing where a problem is, and when it is likely to be repaired, can help
scientists develop contingency plans. In addition to making manual trouble reporting and resolution
easier, a network measurement infrastructure can assist network operators with the day-to-day
monitoring tasks that can automatically find and report problems.
Waiting for trouble reports from users before noticing a problem is another serious issue with
today’s complex network. While a typical operations staff quickly notices and fixes a major outage or a
problem with a well-used application, a niche connection or application may fail for weeks or months
before a trouble report makes it into the Network Operational Center (NOC). See for example [xxvi]
where dramatically reduced throughputs went un-noticed and un-reported for more than two months,
yet when reported took only hours to fix. In the mean time, the end-user is frustrated and unable to
4
effectively use the network to perform a specific task.
At a higher level, the impact of this work on society will mirror that of the Internet itself; by
making networks easier to operate and use, scientists and end-users alike will have an improved
experience. This translates to scientific and commercial benefits from the ability to more effectively use
existing applications or take advantage of new ones [xxvii].
Today, numerous scientific disciplines have developed globally distributed work environments that
depend on the network. Some examples include:

The international High Energy and Nuclear Physics (HENP) community is nearing completion
of the Large Hadron Collider (LHC) [xxviii] facility located at CERN in Switzerland. The LHC
will allow thousands of scientists, engineers, and university professors access to petabytes of
particle physics data. Data will be stored at multiple national repositories and processed at
dozens to hundreds of sites around the globe. Both NUST and the National Centre for Physics
(NCP) at Quaid e Azam University and others are building computer clusters to be used for
simulations and analysis for LHC and others. Without highly reliable and high performance
network connections to CERN, Europe and the US, these clusters will have limited global
impact as they will be unable to replicate and transfer the large amounts of data required for
simulation and analysis.

Cisco (Dr. Horst Dumke and Dr. Masum Hassan) in collaboration with NIIT (Dr. Arshad Ali)
has been aggressively pursuing the establishment of a ‘Health e-Grid’ [is there a REF]. Due to
the fact that sufficient trained medical professionals are not available in Pakistan (even in urban
areas), providing health facilities to the population (of 160 million with a growth rate of 2.09%)
in general is a challenging task. The intention behind the Health e-Grid project is to setup a
tele-medicine infra-structure so as to provide basic medical facilities to the population in remote
areas. A step towards providing affordable health care to Pakistani public is to make use of Grid
technologies to provide the facility of telemedicine. Given the critical nature of such Grid
applications, the setup, management and maintenance of PERN – the network over which the
applications are intended to execute – is of vital importance.

The Virtual University [xxix] of Pakistan delivers education through a judicious combination of
broadcast television and the Internet. The lectures and miscellaneous literature is made available
over the PERN in the form of streaming media and documents/archives from the Virtual
University’s servers. Here too the predictable behavior of the underlying network is desirable
which can only be achieved if it is suitably monitored, the network is reliable and anomalies are
either identified in time to limit major disruptions..

Organizations such as Pakistan Agricultural Research Council, Agriculture University
Faisalabad, Agriculture University, Peshawar have been collaborating under the AgroInformatics [xxx] initiative and have achieved significant results. Such initiatives have only been
possible due to the availability of means to conduct collaborative research. Existence of
networks such as PERN encourage such collaborations by providing suitable means for
communications among the collaboration.
On a more technical level, the rapid detection and correction of network performance problems and
infrastructure faults represent unresolved problems facing all these scientific communities. It is difficult
to overstate the amount of effort that large-scale distributed projects such as these spend on network
debugging and performance tuning. That this effort is duplicated across projects represents a significant
waste of time and energy. Moreover, many scientists are forced to become part-time network engineers,
which is an inefficient use of their time and effort.
Therefore, a network monitoring infrastructure should focus on the following:
 Implement techniques to share network performance data across domains to enable a broader
snapshot of network performance with the end-to-end view.
 Enable and accommodate new types of analysis that are continually being developed.
Sometimes, these are done using completely new tools that generate information on completely
5
new metrics. Often, they represent new ways of correlating existing diagnostic data types.
 Be easily adaptable to changes in network technology to support new devices and provide
useful diagnostic data. This may include ease of extensibility to new data sources – new tools
are produced frequently and the system must not be biased toward any particular tool.
 Secure, policy-based access: the ability to provide protection for who can access what and under
what conditions at a local level is critical for a single system framework to be accepted.
 Community-driven: the architecture of the system must be completely open (and open source)
to encourage the reintegration of extensions and the piecemeal upgrading of modular
components.
Another aspect of network performance is that Network Operational Centers (NOCs) typically are
focused on monitoring the performance of their own network domains. However, real Internet users
will have to traverse many different domains in order to do their work. As such, the typical end-to-end
performance experienced by real network users, is often nowhere near that which NOCs would assume.
Example limits in the performance of end-to-end experiences include:
 Badly tuned network components (including mismatched speed or duplex issues, stack
limitations or even TCP algorithmic limitations).
 Routing problems; including mis-configured routers and switches; non-optimal routes; poor
backup routes; flapping etc; all causing unpredictable performance.
 Overloaded networks which have been badly provisioned to support the traffic that upon it.
 Denial of Service attacks; maintenance; power problems; firewall limits; port blocking;
congestion; improper host configurations; application problems.
Real-life examples of all of these can be found in the SLAC Case Studies referenced above.
3(c) Prior Experience / Capability
The perfSONAR consortium initiated in partnership by Internet2 [xxxi], the European Union-funded
GÉANT2 project [xxxii], and DoE Energy Sciences Network (ESnet) [ xxxiii], has been working, in recent
years, to provide an open set of protocols and a reference implementation to address cross-domain
sharing of network measurements and metrics. SLAC recently joined the consortium - providing their
experience and skills in deploying the PingER and IEPM-BW network monitoring infrastructures; their
expertise in network data mining and analysis; as well as their close involvement with HENP [xxxiv] and
the LHC [xxxv].
The perfSONAR project is focused on building open source, flexible, modular, and extensible
performance middleware to greatly simplify the process of gathering and sharing network performance
information across multiple administrative domains to simplify the process of debugging network
issues and to provide performance data to network-sensitive applications without redundant
measurements. Early prototypes of the perfSONAR framework are deployed in Europe and in North
and South America and serve as a central component of the network monitoring functionality for the
global network dedicated to serving the LHC project. The rapid adoption of the early prototype of the
perfSONAR system by various NRENs and the LHC project is a testament to the need that it fills.
The perfSONAR project originated with the desire to unify the efforts of Internet2’s End-to-End
Performance Initiative Performance Environment System (E2E piPES) project [xxxvi] and the EU’s
GÉANT2 Joint Research Activity on monitoring and measurement (GN2-JRA1) [xxxvii], ultimately
involving parallel efforts in the U.S. DoE’s ESnet. The desired result of this project, a common
performance middleware, is referred to as the perfSONAR framework. This project seeks to enable
consistent access to network performance data across a large fraction of the world’s advanced research
and education networks. The effort is in its second year of funding in the EU and receives a small
amount of seed money from Internet2 and ESnet in the United States. Some components of this
framework exist in prototype form, but much remains to be done.
This framework specifically defines a federated network measurement infrastructure that can be
used by a large number of research scientists and scientific collaborations. The perfSONAR project is
6
still at a very early phase, with much work to be done yet, but it is beginning to have a significant
impact already and to generate interoperable, independent development of additional services, which is
a testament to the level of community support.
perfSONAR defines a series of mid-level services that can be used to create a measurement
infrastructure. It does not mandate the use of a specific tool or set of tools to be used to generate or
capture measurement data. Rather, it defines a standard XML-based storage schema that allows
multiple tools to generate and consume data. This increases the usability and reach of these tools,
making them more applicable to a larger number of potential users. perfSONAR does not require realtime intervention to deploy tools or to coordinate the data collection process. Instead, a standard
authentication mechanism allows interested parties (e.g., end-users, scientists, dedicated support staff,
network operators) to pre-register themselves in a domain-managed database. Once registered, these
users can present their credentials to a remote domain’s federated authorization service and, if approved
(according to locally-determined policies, and home institution defined identity), they can begin
troubleshooting a problem.
In summary, the perfSONAR framework will ultimately:
 Be easily extensible to new types of measurement and analysis tools. Tool developers will be
able to focus on how the tool operates, not on how to deploy the tool widely enough for it to
become useful.
 Scale to global size. Multi-national science communities will be able to focus on science, not
just run networks.
 Contain flexible policy for sharing across administrative domains. Local domains will retain
control over the policies that define how specific resources can be accessed and what data will
be shared with whom according to uniform, organization-agreed-upon policies, not ad hoc
decisions based on personal relationships.
 Use common data exchange formats. The OGF [xxxviii] NM-WG [xxxix] schemata will be used to
ensure that different tools and archives can exchange data effectively.
 Use common discovery mechanisms. Users will be able to find measurements points and
archival data to assist in troubleshooting an application’s behavior.
 Use generic service components for tracking resource utilization and user authorization to
acquire those resources for performance testing.
 Piggyback on existing federated trust authentication infrastructures.
We believe the perfSONAR framework provides the necessary services and infrastructure to
facilitate a rich and extensible monitoring system for PERN2 from which further network research and
opportunities can arise.
Various funded projects in the past have failed to reach critical mass in the realm of network
monitoring due to their lack of open source and open community traits. Furthermore, projects, such as
AMP, MonALISA [xl], IEPM-BW, PingER and Surveyor, have attempted to bundle data generation,
data sharing, and analysis with visualization in an attempt to do everything. However, they have been
hampered by the relative lack of standards for sharing performance data, limiting the breadth of data
(both in type and deployment) available to be consumed. Many members of the perfSONAR
development team have been directly involved with creating or using these tools and the lessons
learned during those developments have been incorporated into the perfSONAR framework.
SLAC has been a leader in network monitoring and performance tuning for many years and has
over fourteen years of computer networking experience in the wide area with experiences ranging from
the deployment of the first Internet in China [xli], capturing the Internet2 Land Speed Record twice [xlii],
winning the Supercomputing Bandwidth Challenge three years in succession (2003, 2004 and 2005
[xliii]), to the monitoring of the digital divide between developed and developing countries [ xliv]. SLAC
also has extensive experience developing and deploying network infrastructures such as the PingER
suite and the IEPM-BW suite – both of which are still collecting data on over 125 countries from over
40 sites throughout the world.
7
With the benefits of decentralized network monitoring provided by the perfSONAR framework,
SLAC has shifted its focus from the deployment and collection of metrics to the analysis and
presentation of network performance. An important aspect to the analysis of network performance data
is the understanding of the baseline performances and the effects of seasonal effects such as the
increase of network traffic during work days and hours.
This is illustrated in the figure below for throughput measurements from SLAC to the University
of Florida, where it is seen (blue line) that at the weekend measured performance is higher and then
oscillates (day down, up at nights) during the week. The attempt to use an exponentially weighted
moving average (light blue smooth line) to predict the performance lags the data and, following the
weekend, the differences are outside the acceptable range (below the orange line) for a sufficiently long
duration (the black line is the number of events falling outside the threshold) that an event is detected.
Figure 2: Detection of anomalous events using the plateau algorithm [REF] from SLAC to U. Florida
The net result is that there is a higher probability for detecting false events at the end of a weekend
or the start of a weekday. This is illustrated in the plot below where we see the number of events
triggered by the simple non-seasonal Kolmogorov-Smirnov [xlv] algorithm is weighted towards 21:00
hours Pacific time (which is 9:00am Pakistan time, or the start of the work day when utilization
increases and congestion starts to get bad).
Figure 3: Frequency of detecting events as a function of time of day using the Kolmogorov-Smirnov algorithm on
available bandwidth between SLAC and NIIT.
Thus for paths with seasonal variations we need to investigate more sophisticated techniques
including Holt-Winters [xlvi] and ARMA/ARIMA [xlvii] models. The authors of this proposal have built
prototypes using Holt-Winters [xlviii] and investigated ARMA/ARIMA [xlix] for forecasting and event
detection. An example of the use is shown in Figure 4. Given the noisiness of the data (dots) it is first
smoothed (blue line), Holt-Winters is then used to forecast the performance (red line of bandwidth
capacity) and provide expected deviations (black lines). If the smoothed data goes outside the
deviations for sufficient number of points then an event is signaled. It is seen that the Holt-Winters
forecast tracks the seasonality of the data, and detects the sudden and persistent drop in performance on
Friday evening/Saturday morning July 31, 2004.
8
Figure 4: Time series of bandwidth capacity measured between SLAC and U. Indiana with forecasting by HoltWinters, and the detection of an event.
The above is a simple example of the types of analysis that network engineers and end-users would
analyze to diagnose a network problem. As the perfSONAR framework enables the collection and
storage of results in a simple and consistent format, it offers new opportunities that will lead to a broad
wealth of network performance data – data that will invariably take a network expert an impossibly
long time to analyze and document. Furthermore, with such abundance of data, it is likely that simple
problems will take a while to finally be detected, or worse still, fail to be detected at all. Therefore, data
mining techniques and new visualizations should be incorporated into the data collection and analysis
to highlight the important features and make it useful and not onerous.
In addition, the proliferation of data would mean that there could be tens of thousands of time
series data of multiple metrics between multiple pairs of hosts; and to determine the scope and locations
of performance problems would be nigh on impossible. This naturally leads to automated systems that
will help analyze, detect, present and report on potential problems – soon after it happens or in some
cases even before the problem occurs through the analysis and forecasting of certain metrics such as bit
error rates between two devices [REF?]. There is therefore a need to reduce the data volume into
manageable and easy to understand formats (tables, graphs etc) whereby network engineers and
operational managers can quickly determine the performance characteristics of their network.
Using example techniques presented above for event detection, this proposal will also focus on the
automated detection, alerting and diagnosis of such network performance problems on a global scale.
This will be done using heuristic models of network fault detection [l] combined with the cross
correlation of events in time series for a given metric for a given path; also other related time series for
different metrics, different target hosts and probe sources; plus information from intermediate points
along the network path(s) looking for shared experiences will be used to eliminate or pin-point
common possible causes. The ultimate goal of such complicated analysis will help increase the
accuracy of problems, reduce the frequency of false positives and provide more diagnostic information
by eliminating possibilities and helping pin-point the possible cause(s). Alerts will be generated in the
form of emails with attached diagnostic information. To reduce the annoyance factor of multiple alerts
we will also use techniques (such as triggering an event state when one threshold is passed and
resetting it when recovery passes another threshold (hysteresis)), and by not un-necessarily repeating
alerts for the subsequent re-detection of the same event.
Over the last two and a half years, SLAC has a proven track record in supervising and training
Pakistani NIIT students both at NIIT and at SLAC to be productive, acquire knowledge and share it and
their expertise to benefit Pakistan/PERN network activities. These students have come from classes that
contain 50:50 ratio of male:female. In the past there have three women students who worked with
MAGGIE and have recently graduated. Numerous interesting and innovative projects have spawned
from this relationship (previously funded under the MAGGIE project [li]) which has developed several
measurement, analysis tools and international case studies available in the public domain. Examples
include: PingER management; IEPM-BW deployment at about a dozen sites; the ABwE measurement
probe [lii]; yearly ICFA SCIC Network Monitoring Reports [liii] giving quantitative, non-subjective
measures of the Digital Divide from an Internet point of view; detailed case studies [liv] of the network
performance within and between the region and the rest of the world for: Pakistan, South Asia, Latin
9
America, Palestine, and Sub-Saharan Africa; and numerous prestigious invited presentations around the
world for example the American Physical Society [lv], ESnet/Washington [lvi], Internet2/Washington
[lvii], ICTP/Italy [lviii], Mumbai/India [lix], Pakistan [lx] and ICTP/Romania [lxi];
SLAC has also hosted visits by NIIT staff and faculty enabling faculty members to gain valuable
experience and promote the research culture in their classrooms. SLAC staff have also visited Pakistan,
learnt in more detail of the needs and possibilities, and shared their expertise and case studies directly
with the students and faculty both of NIIT, other universities in Islamabad/Rawalpindi, and with PERN,
HEC and related institutions. This has resulted in useful observations and recommendations that have
been made to PERN and HEC among others.
3(d) Scope and Objectives
Given the need of network monitoring and the analysis of network data in order to make it useful,
the scope of this proposal is threefold:
 To apply the perfSONAR framework to PERN, this will involve amending and or creating new
services, from the existing perfSONARservices, which are tailored towards the specific
requirements of the Pakistani research network – i.e. the software.
 Develop new and innovative presentation, reporting, network problem detection and alerting
techniques based upon the perfSONAR framework using the experience gained from previous
projects and make them production quality for use on PERN2 – i.e. the analysis.
 To foster the partnership between NIIT/Pakistan and the SLAC/U.S. to improve the quality and
relevance of Pakistani higher education in science and technical fields.
This project also aims to develop new forecasting tools and identify network anomalies as a means
by which network problem detection can be extended. Building on analysis techniques used at SLAC,
the forecasting will use advanced statistical models such as Holt-Winters and ARMA/ARIMA.
To assist in divide and conquer techniques for diagnosis and pin-pointing of network performance
issues, we will also work with PERN to install one or more nodes in their network. A major purpose of
these nodes will be to make on-demand measurements (e.g. ping, thrulay) with sufficient
Authentication, Authorization and Auditing. These will also assist in dividing possible problem sources
up to assist in pin-pointing the cause. We will ensure the software is configurable to meet different
sites’ configurations. In addition we will work closely with PERN to get secure access to backbone
router/switch information (e.g. utilization, errors, configuration information such as location etc.).
Bringing PERN into the project will help the whole Pakistani educational and research community
join and share experiences with a growing community of worldwide NRENs. In addition, across these
NRENs, there will be common monitoring and assisted diagnosis to assist users in effectively using
their network connections. This will be critical for users such as scientists and researchers using the
NCP [lxii] and NUST [lxiii] clusters.
The deployment of a perfSONAR installation for PERN2 will be staged. Initial end-site
installations will be at SLAC and NIIT. These will help to create documentation drafts, and installation
procedures while improving the deployability of the framework. Following this we shall install at endsites where we have existing strong partnerships. These include the National Centre for Physics (NCP)
at Quaid e Azam University (QAU) and COMSATS where there are strong scientific programs,
concentrations of senior scientists and Grid activities - we believe that application at these sites will
offer the best use-cases for the advanced technologies and techniques outlined in the next sections. We
are working to extend our partnerships to include sites in Karachi (e.g. SSUET and/or FAST-NU) and
elsewhere in Pakistan with similar strengths.
Typically the machine to host the monitoring software at a site will be provided and administered
by the site with sufficient power and connectivity. Using open source software and operating systems
(Linux), we will reduce the cost of such machines whilst also increasing their security. Persuading endsites to contribute their own machines will also reduce the site-specific administration and
security/deployment issues while improving the “buy-in” partnership of the end-site personnel.
The expertise of SLAC’s, and more recently NIIT’s, involvement in global network monitoring
10
will be applied to demonstrate the middleware components/services of the perfSONAR framework.
An important part of this proposal builds on SLAC’s and NIITs continued commitment to help
develop the intellect, skills and ability of Pakistani students. It does this by training NIIT graduate
students to contribute to research and development of computer networks to benefit the Pakistani
research and education community. Selected students will spend time at SLAC, which is highly
regarded as one of the foremost research facilities in the world; and have access to high performance
computing and networking facilities not currently available in Pakistan. They will also have access to
advanced high-speed networks in the US and Europe, and will work with acknowledged experts in the
network monitoring field. Thereby they will be developing highly skilled human resources for Pakistan
by conducting applied research and developing network monitoring and end-to-end network
performance measurement tools/infrastructure. This will greatly increase their skills in very relevant
areas for Pakistan and not only will they contribute to the development of new technologies but also
share the experience and will be in a position to contribute positively to the Pakistani society and
economy.
As a tentative schedule, in the first year we intend to identify, extend and customize, package and
deploy and validate the necessary performance services across Pakistan. In the second year we intend to
apply and evaluate mechanisms that will be productive in detecting and pin-pointing network
performance problems, of which in the third year we will ensure that the most useful are hardened into
production quality services that will be used across PERN and potentially worldwide.
3(e) Methods
The primary objective of this proposal is to deploy, enhance and customize perfSONAR
middleware services for an Autonomous System (PERN2) in Pakistan. In addition to this we intend to
analyze and evaluate algorithms for network weather forecasting, event detection and diagnoses. It will
deal with the deployment, extension of the services and integration of new tools into the perfSONAR
framework.
The main focus of this proposal is to utilize the expertise of SLAC’s history in network monitoring
in order to help guide students at NIIT to understand and contribute effectively to the global
perfSONAR framework, and also towards building a useful network monitoring framework for
Pakistan. Collectively, a series of perfSONAR modular services will be developed and deployed to
provide the performance middleware upon which new tools and analysis service will monitor important
devices along the PERN infrastructure and provide end-to-end performance analysis by being deployed
at select academic institutions around Pakistan:
 Measurement: Measurement Point (MP) services will be developed to provide access to active
and passive network monitoring tools available on PERN. They will create and/or publish
monitoring information related to active and passive measurements. Here, we intend to
investigate suitable network monitoring tools required to gather network performance statistics
for analysis and determine their usefulness and feasibility. Existing tools such as ping,
traceroute, iperf, SNMP [lxiv] utilization (Router/Switch utilization), BWCTL [lxv], Thrulay and
OWAMP [lxvi] will be deployed to provide the core performance metrics that will allow problem
detection and analysis.
 Storage: Measurement Archive (MA) services will be deployed to allow the storage of MP data
that will provide historical information regarding the performance of the network. This is an
important service that will provide the necessary data to determine trends for forecasting and
anomaly detection.
 Topology Service: It is a non-trivial task to engineer the network without having an
understanding of the dynamic nature way in which network paths diverge. Snapshots of how the
complex algorithms enable the Internet to remain interconnected results in the network
topology. This service will provide the information regarding the topology of the network. This
topology will be used extensively in visualization of the weather maps which will help network
engineers to analyze the network efficiently. It will also provide the data from which problems
in network paths can be easily detected and investigated.
11

Decentralized discovery: Maintaining the list of services manually or having static labels for
them is not suitable for a dynamic environment. Thus it is reasonable not only to have a lookup
service, but also a decentralized lookup service to determine the access points the services.
MP’s, MA’s and topology services will register with. The lookup services will provide DNS
[lxvii] like mechanisms to discover the (virtual) location of the various perfSONAR services.
 Security: It is apparent that sharing information regarding Autonomous Systems with users
without suitable Authentication, Authorization or even Accounting (AAA) is not a reasonable
concept. Thus there is a need to provide suitable AAA services to the infrastructure. This would
allow for authorized access to trusted user groups only with a provision for logging the events.
Building upon the perfSONAR concepts, it will utilize existing efforts made by Shibboleth
[lxviii] and eduGAIN [lxix] to provide identity management using existing SAML [lxx] standards.
The next major phase is to provide reporting and diagnostic services such as aggregation and
summarizations of the relevant performance measurement information, and to visualize it in a manner
that is in accordance with the best practices. This requires that MA’s have been deployed and
accessible such that performance metrics can be obtained. In this regard, we intend to develop and
integrate:
 Anomaly Detection and Diagnosis Services - Currently, diagnosis of network problems
requires much administrative manpower and time to determine the cause of the problem(s). The
need is to quickly and automatically identify and diagnose network problems and dramatically
decrease the period that users experience degraded performance. This aims to automatically
gather relevant information, and use heuristical analysis to enable location (e.g. network or host
issues), identification (narrowing down of the cause), and verification (double-checking against
maintenance tickets etc.) of events.
 Alert Service - notify relevant network administrators in the event of an anomaly. Some basic
functionality is already in place to provide alerts within the IEPM-BW framework when
performance changes occur. This project will both provide a more generic method to the
automated analysis of network performance data, and also investigate and implement advanced
algorithms for such analysis and reporting
 Network Performance Forecasting - The prediction of network performance will greatly aid
large scale data replication applications. However, such techniques are currently not very well
understood. This project will investigate and report upon techniques to provide reliable
forecasts of network performance based upon past performance.
 Reporting – The provision of manager level reports on the various network performances is
necessary to help network managers make important choices in the identification of potential
network problems and divert necessary resources to those parts of the network. Similarly, high
level governmental reports should be provided to offer guidance on the International health of
Pakistani’s Internet.
NIIT students under guidance from SLAC and NIIT staff will design, develop, test, integrate, install,
document and support network measurement, analysis and presentation tools, plus infrastructure
management tools. In addition selected NIIT graduate and PhD students will spend a year at SLAC
working closely with SLAC’s experts in a world class research center, and take courses at Stanford
University. In addition it will provide opportunities for the NIIT faculty to visit the high quality
research environment at SLAC and acquire the latest trends in network and related technologies.
Finally it will enable SLAC staff to visit Pakistan, learn in more detail of the needs, and share their
expertise, and vice-versa.
3(f) International Cooperation
The division of effort between Pakistan and the U.S. is optimal. The co-supervision of NIIT
students and their engagement in important network monitoring projects with an international
dimension adds a dramatic widening of their experience. Choosing students at NIIT to be involved in
this project and then further selecting just the best to spend time at SLAC is an enormous incentive.
The students visiting SLAC will work with leading network experts at a world class facility, experience
12
tuition from world renowned professors and should become leaders in their field.
This way, not only will the student and faculty contribute to the development of new technologies
but they also share their experiences and are in a position to contribute positively to the Pakistani
society and economy.
As such all funding for this proposal is aimed towards supporting student activities and
contribution and is provisioned with approximately one-third / two-thirds split of the stipend costs of
the students. The members of this proposal in both the US and Pakistan offer their expertise and time
gratis as a commitment to their dedication towards this project.
3(g) Relevance
Even after embracing information technology for more than over a decade, Pakistan lacks in the
availability of sufficient skilled human resource. A number of reasons may be attributed to this lack of
quality human resource. A major attribute to this situation may be the lack of opportunity and
resources. We believe that the the project MAGPIE addresses such issues (and achieves the funding
program’s objectives) in the following manner:
 This project will contribute to the nation’s development of human resource as the students and
faculty working under this project shall be given the opportunity to gain knowledge of research
and development in the domain of network performance monitoring as well as valuable
experiences and best practices by working with renowned institutes such as SLAC. During a
period of three years it is estimated that the direct beneficiaries of the project will include two
PhDs, two Masters, eight undergraduate students and four faculty/staff members. However the
project will have a multiplier effect on approximately sixteen faculty members and several
research associates, undergraduate and post-graduate students as a consequence of interaction
with the direct beneficiaries.
 The local industry such as Micronet Broadband Pvt. Limited [lxxi] shall also benefit from the
experiences since they are in close collaboration with NIIT regarding three development
projects (maintenance of network-route consistency, dealing with DoS attacks on the service
network and open software for network setup and management) to fulfill their local
requirements.
 This project will also enhance the capabilities of PERN to function as a network with over 60
universities throughout the country. The collaborators of this proposal believe that just
connecting the universities is not sufficient; planning maintenance and continual improvement
of service levels is also equally important, as is the ability to pro-actively respond to problems.
With the team’s rich expertise in Network Monitoring and Measurement of the digital divide,
the analyzed data would be highly valuable to the decision makers in the government.
 As a consequence of this project the participants will not only gain knowledge of network
performance measurement and analysis, but will also have the experience of working on highperformance networks. This trained human resource will then be of immense importance to
diverse organizations in the local industry such as Internet service providers, telecomm
operators as well as the software industry.
3(h) Results Statement
Design and deploy a perfSONAR compliant infrastructure on PERN2 that will offer very valuable
and varied network performance data across both the backbone and selected end-sites across Pakistan.
Using this data, design innovative and production quality mechanisms to present, analysis,
diagnose and pin-point network performance problems that will be beneficial to both network engineers
and Internet end users.
Pakistani students and faculty who participate will gain experience in high performance networks
and innovative research in networks and their monitoring; and be enabled to contribute to Pakistani
education and growth.
13
3(i) Additional Benefits
Building a large international community invested in deploying the perfSONAR measurement
framework is as important as developing the actual software. The perfSONAR framework is being
developed in an open community by consensus, with all community-developed code given a BSD-style
open-source license. There is thus no impediment to contributions from Pakistan or Pakistan taking
benefit from the developments from this project.
Academic institutes participating in this project will have access to a large scale monitoring
network in Pakistan which will provide them practical hands-on experience. Students and researcher
from these institutes shall be able to incorporate their own research ideas into this infrastructure.
This infrastructure will make it easier for educators to bring the network into the classroom. Early
prototype components of the perfSONAR system have been featured in courses at the University of
Delaware [lxxii]. Daily use of the network for routine teaching activities depends on a network
infrastructure that can meet the needs of the teaching application. A perfSONAR-enabled network will
allow educators and support staff to easily verify and demonstrate that the network is operating
properly.
Members of the perfSONAR consortium are already engaged with resolving performance issues on
production networks. By continuing to work with operations staff, local administrators and faculty, the
team will promote the tools and the advantages of self service over waiting for third parties to run tests.
For example Georgia Tech. and SLAC are deploying campus wide network monitoring infrastructure.
These infrastructures will be perfSONAR enabled, allowing faculty and central support staff to view
performance and schedule tests within and beyond campus.
This proposal will help build bridges across the world, extend education to both male and female
students, reduce misunderstanding and help reduce radical, fundamentalist indoctrination of hate.
14
3(j) Budget (in equivalent US $) (For Year 1)
Pakistan Side
Requested
Approved
Items requested
US Side
Requested
Approved
Equipment (Attach Proforma invoice)
Four deskside computers & monitors for students
$3450
Consumables
Services (Attach Proforma invoice)
Travel
Domestic travel (2 trips/year)
$3450
Support personnel
Four graduate student for 12 months ($900/mo from
SLAC)
$51568
Miscellaneous
Tuition
TOTAL US $
$58468
15
Budget (in equivalent US $) (For Year 2, if requested)
Pakistan Side
Requested
Approved
Items requested
US Side
Requested
Approved
Equipment (Attach Proforma invoice)
Compute server for analysis and data storage
$1785
Consumables
Services (Attach Proforma invoice)
Travel
Domestic travel (2 trips/year)
3571
Support personnel
Four graduate students for 12 months ($932/mo
from SLAC)
$53373
Miscellaneous
TOTAL US $
$58729
16
Budget (in equivalent US $) (For Year 3, if requested)
Pakistan Side
Requested
Approved
Items requested
US Side
Requested
Approved
Equipment (Attach Proforma invoice)
Consumables
Services (Attach Proforma invoice)
Travel
Domestic travel (2 trips/year)
$3696
Support personnel
Four graduate students for 12 months ($964/mo
from SLAC)
$55241
Miscellaneous
TOTAL US $
$58937
17
Budget (in equivalent US $) (TOTAL REQUESTED for all years of project)
Pakistan Side
Requested
Approved
Items requested
US Side
Requested
Approved
Equipment
Four deskside computers & monitors for students
Compute server for analysis and data storage
$3450
$1785
Consumables
Services
Travel
Domestic travel (2 trips/year)
$10,716
Support personnel
Four graduate students for 12 months each year for
3 years
$170,943
Miscellaneous
TOTAL US $
$186,595
OTHER FUNDING. Please list the source and amount of any other funds received or applied for
to support this project:
18
3(k) Executive Matters / Budget Requirements
i. Timetable (Please indicate each major step in project evolution referring to the time schedule)
2008
ID
Task Name
Q1
1
Deployment of the perfSONAR framework for PERN2
2010
Measurement – Measurement Point (MP) services
will be developed to provide access to active and
passive network monitoring tools available on
PERN2.
288d
3
Storage – Measurement Archive (MA) services will
be deployed to allow the storage of MP data that will
provide historical information regarding the
performance of the network.
432d
4
Topology – The topology service will be deployed to
provide the information regarding the topology of the
network.
288d
5
Discovery – The lookup service shall be deployed to
provide DNS like mechanisms to discover the
(virtual) location of the various perfSONAR services.
288d
6
Security - Suitable services of Authentication,
Authorization and Accounting (AAA) shall be
deployed for the management of the perfSONAR
monitoring infrastructure.
288d
7
Integration and Testing
144d
Algorithms for Network Performance Monitoring,
Event Detection and Diagnosis, and extension of the
perfSONAR framework
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
764d
2
8
2009
Duration
686d
9
Anomaly Detection and Diagnosis Services
288d
10
Alert Service
288d
11
Network Performance Forecasting
432d
12
Reporting Service
288d
Figure 5 Time line of project tasks
ii. Request justification (Please provide detailed justification for each budget item requested)
Support Personnel:
The twelve graduate students who will be visiting SLAC for one year each, will be funded from the
SLAC side at $900 per month.
Miscellaneous Expenses:
Over the three years we will need a workstation and screen for each of four students currently at
SLAC. Since workstations have a rough lifetime of three years we are asking to procure four workstations
each with a flat screen in the first year. We estimate the cost of each workstation and and screen at about
$750. In the second year we will procure a server to host the data and analysis tasks at a cost of about
$1500.
All costs will be escalated at 3.5% for years two and three.
The Stanford University fringe benefit rate of 3.8% for graduate students has been applied to salary
costs,
SLAC’s indirect costs will be charged at 15% to all items, following the proposal instructions,
although SLAC’s normal indirect rate is 39%. Dr. Les Cottrell, head of the Network Computing Group,
will direct the project at SLAC (10% effort / no cost to the project). Other researchers (35% FTE/no cost
to project) will provide coordination, guidance, training, quality control and integration.
SLAC is a department of Stanford University, under a Management and Operating contract with the
US Department of Energy. All SLAC expenditures under this grant are incurred under the cost principles
19
governing SLAC as outlined in the DoE/SLAC contract.
iii. Travel details (Please indicate number, duration, timing, and justification for each visit proposed for each side)
Research Students visit / stay at SLAC (US): A major part of this collaborative effort is to provide
students with high quality research environment. Nine students are to be sent to SLAC over the three year
duration for research visits of one year’s duration for each student. During this visit students will have a
chance to grow in an environment which has a proven track record of basic and applied research. During
this visit students will also be able to take courses at Stanford University.
NIIT Faculty visit/stay at SLAC for collaborative meetings: This collaborative project requires
frequent meetings between NIIT and SLAC mentors and students. Most of the communication is through
e-mails, phone calls and video conferences which are very useful but not enough. It is required that
faculty of NIIT working on this project visit SLAC for a period of 2 weeks each year so that faculty
members are able to guide students in a better fashion.
SLAC supervisors visit to NIIT: Some students working with this research group will have a chance
to visit SLAC as internees. For guidance of other students it is required that a SLAC mentor visits NIIT
once a year for a period of two weeks each year, so that even if a student does not visit SLAC there is a
strong interaction with existing students and new students can be attracted and introduced.
Conference Travel & per diem: We are anticipating two publications per year in this project. We
have decided to publish one of those in international conferences to establish the usefulness and
importance of our research. We have also decided to publish one of the research papers in a domestic
conference so that other Pakistani institutes and students also benefit from our work.
Local Pakistan travel: This category involves travel by Network Assistant or research student for the
installation/upgrade/ deployment of the server(s). This is an ongoing activity which shall continue for the
whole duration of project.
SLAC requests funding to cover the cost of two domestic (U.S.) trips/year to attend conferences,
present findings, meet with and share information with collaborators in perfSONAR.
iv. Additional notes (Please provide additional appropriate information, if any)
3(l) Curricula Vitae (Please attach brief CVs—1 or 2 pages each—for all Pakistani and US participants. Please
do not include lengthy publications lists or copies of publications.)
Co-PI (Pakistan):
Prof. Dr Arshad Ali is a senior IT professional and academicians. He completed his PhD studies in
1992 from University of Pittsburgh, USA in the Design, Simulation and Fabrication of Optical
Waveguides for Optical Computers. He has over 26 national and international publications to his credit.
Dr Arshad has been awarded Pakistan Academy of Sciences and COMSTECH gold medal for IT
research. Currently he is working as Dean, NUST Institute of Information Technology (NIIT),
Rawalpindi.
Dr Arshad enjoys good rapport with IT industry which helped in establishment of CISCO Local
Academy program, attracted donation of state of the art computer Lab from INTEL, USA and a teradata
Lab from NCR Pakistan for NUST Institute of IT (NIIT).
Dr Arshad initiated research collaboration with Center for European Nuclear Research (CERN),
Switzerland and earned the Associate Institute status of CMS-CERN for National University of Sciences
& Technology (NUST). Dr Harvey Newman from CALTECH USA (29 faculty members include Nobel
Laureates) has committed 40,000 US dollars per year grant to strengthen this research collaboration
20
initiative. The research collaboration with Stanford University (SLAC Project), USA has also helped in
attracting 100,000 US dollars funding from US State department.
Dr Arshad formed a joint consortium with University of the West of England UK, Beijing Institute of
Technology China, University of Savoie France and NUST Pakistan which attracted 400,000 Euro
research funding from European Union. He is actively pursuing research in Distributed computing and
Grid Technologies in collaboration with University of Melbourne Australia and University of Portsmouth
UK. Prof. Dr Arshad is also contributing in launching of open source resource center in collaboration
with Pakistan Software Export Board, Comtec (Communication Technologies) Japan and NUST,
Pakistan.
Co-PI (US):
Dr. R. Les. Cottrell received his BSc (Hons) in 1962 and his PhD in Nuclear Physics in 1967 from
Manchester University, England. He then joined the Stanford Linear Accelerator Center (SLAC) as a
research physicist in High Energy Physics, focusing on real-time data-acquisition and analysis in the
Nobel 1990 prize winning group that discovered the quark. In 1972/3 he spent a year’s leave of absence
as a visiting scientist at CERN in Geneva, Switzerland. In 1979/80 he spent another year’s leave of
absence this time as a visiting scientist at the IBM UK Laboratories at Hursley, England. While at IBM he
developed a dynamic graphical cursor that was granted United States Patent 4,688,181.
On returning from IBM UK, in 1980, he became the manager of SLAC’s computer networking. In
1982 he became the Assistant Director of SLAC’s Computer Services (SCS). From 1995-1997 he was the
Acting Director of SCS. He is currently the Assistant Director of SCS and leads SLAC’s computer
networking, telecommunications, and remote collaboration support groups. He is also SLAC’s
representative on the ESnet Site Coordinating Committee (ESCC), the chairman of the International
Committee on Future Accelerators (ICFA) Standing Committee on Inter-regional Connectivity (SCIC)
Network Monitoring Working Group. He has served on many advisory groups such as for the
Superconducting Super Collider (SSC), the American Institute of Physics, IHEP/Beijing, Internet2, and
FNAL, as well as technical committees such as chairing the ESCC Network Monitoring Working Group,
and being a member of the Global Grid Foundation’s Network Monitoring Working Group. He is also the
PI of the DoE funded Internet End-to-end Performance Monitoring (IEPM) project which has attracted
funding of almost $2M since 1997.
He was the leader of the effort that in 1994 established the first permanent Internet connection to
mainland China. He was co-PI of teams that won the Internet2 Land Speed record twice, an achievement
listed in the Guinness Book of Records (2004). He was a co-leader of teams from Caltech and SLAC and
other institutes that won the prestigious SuperComputing Bandwidth Challenge three years in succession.
He is the SLAC PI of the DoE funded Terapaths project, the NIIT/MAGGIE project, and the
collaboration with ICTP, Trieste.
4. References
i
M. Desai, S. Fukuda-Parr, C. Johansson, F. Sagasti, "Measuring the Technology Achievement of
Nations and the Capacity to Participate in the Network Age", Journal of Human Development, Vol. 3,
No. 1
ii
H. Newman, “ICFA SCIC Report for High Energy Physics” available at
http://monalisa.cern.ch:8080/Slides/SCIC2006/ICFASCICReportV17_020706.doc
iii
“Network Problem Cases”, available at http://www.slac.stanford.edu/grp/scs/net/case/html/
iv
perfSONAR, available at http://www.perfsonar.net/
v
LBL, “tcpdump”, available at http://www.tcpdump.org/.
vi
NLANR, “OCXMON”, available at http://moat.nlanr.net/Papers/ieee-comms-nlanr-html/node4.html.
vii
Cisco, “Netflow”, available at http://www.cisco.com/warp/public/732/Tech/nmp/netflow/index.shtml.
viii
“Web100”, available at http://www.web100.org/.
21
NLANR, “Iperf”, available at http://dast.nlanr.net/Projects/Iperf/,
Internet2 “Thrulay”, available at http://sourceforge.net/projects/thrulay/.
xi
Internet2, “Network Diagnostic Tool”, available at http://e2epi.internet2.edu/ndt/
xii
Internet2, “Network Path and Application Diagnosis”, available at http://web100.internet2.edu:8200/.
xiii
NLANR, “Introduction to the NLANR AMP Project for HPC sites”, available at
http://amp.nlanr.net/AMP/
xiv
Advanced Network Services, “Surveyor”, available at http://www.advanced.org/surveyor/.
xv
IEPM: “Internet End-to-end Performance Monitoring - Bandwidth to the World (IEPM-BW) project”,
available at http://www-iepm.slac.stanford.edu/bw/.
xvi
W. Matthews and R. L. Cottrell “The PingER Project: Active Internet Performance Monitoring for the
HENP Community”, IEEE Communications Magazine, May 2000.
xvii
RIPE, “Test Traffic Measurement Service”, available at http://www.ripe.net/test-traffic/index.html
xviii
HEC, "Request for Proposal (RFP) for Establishment of 10GbE Metro Area Network for PERN2 in
Islamabad/Rawalpindi Region", Higher Education Commission, H-9 Islamabad, document
HEC/RFP/PERN2/564-2006, available at
http://www.hec.gov.pk/new/eReforms/download/RFP%20for%20Metro%20Network%20for%20PERN%
20in%20Isb.pdf
xix
Aga Khan University, “Clinical Epidemiology Unit”, available at http://www.aku.edu/research/ceuonprj.shtml
xx
Pakistan Medical Research Council, “Research Activities”, available at
http://www.pmrc.org.pk/researchactivities.htm.
xxi
CERN, “Pakistani Physics”, available at http://cerncourier.com/main/article/39/7/21.
xxii
National University of Computer and Emerging Studies, “2nd Workshop on Agro-Informatics”,
available at http://www.nu.edu.pk/NewsDetails.aspx?nid=78
xxiii
Associated Press of Pakistan, “Media University in Pakistan – a significant leap into the future”,
available at http://www.app.com.pk/en/index.php?option=com_content&task=view&id=5631&Itemid=2
xxiv
National College of Arts, Lahore, “Research and Publication Centre”, available at
http://www.nca.edu.pk/rpc/main.htmlhttp://www.nca.edu.pk/rpc/main.html.
xxv
“Virtual Iniversity of Pakistan”, available at http://www.vu.edu.pk/..
xxvi
SLAC, “Throughput from SLAC to Caltech reduced by a factor of 5”, available at
http://www.slac.stanford.edu/grp/scs/net/case/caltech/
xxvii
See for example: Wachovia, “Wachovia Benefits from Improved Inter-Office Collaboration with
Cisco TelePresence”, available at http://newsroom.cisco.com/dlls/2007/ts_060407.html.
xxviii
CERN, “Large Hadron Collider”, available at http://cern.ch/lhc/.
xxix
“Virtual University”, Pakistan, http://www.vu.edu.pk/
xxx
“Agro-informatics”, http://www.agroit.com/reports.html
xxxi
“Internet2”, available at http://www.internet2.edu/.
xxxii
“GEANT2”, available at http://www.geant2.net/.
xxxiii
DoE, “Energy Sciences Network”, available at http://www.es.net/.
xxxiv
SLAC, “BaBar Public Information & Visitor Pages”, available at
http://www.slac.stanford.edu/BFROOT/.
xxxv
SLAC/ATLAS, “The US ATLAS Western Tier 2 Computing Center”, available at
http://wt2.slac.stanford.edu/.
xxxvi
Internet2, “E2E Performance Initiative Performance Environment System Architecture”, available at
http://e2epi.internet2.edu/e2epipes/
ix
x
22
GEANT2, “Joint Research Activity on monitoring and measurement (GN2-JRA1)”, available at
http://wiki.perfsonar.net/jra1-wiki/index.php/JRA1_Main.
xxxviii
“Open Grid Forum”, available at http://www.ogf.org/.
xxxix
“Network Monitoring Working Group”, available at http://nmwg.internet2.edu/.
xl
Caltech, “MONitoring Agents using a Large Integrated Services Architecture”, available at
http://monalisa.caltech.edu/
xli
R. L. Cottrell, C. Granieri, L. Fan, R. Xu, Y. Karita, “Networking with China”, CHEP94, also SLACPUB-6468, April 1994.
xlii
SLAC, “Internet2 Land Speed Records”, available at http://www-iepm.slac.stanford.edu/lsr2/.
xliii
“Global Lambdas for Particle Physics Analysis”, available at http://wwwiepm.slac.stanford.edu/monitoring/bulk/sc2005/hiperf.html
xliv
Edited by R. L. Cottrell, “ICFA SCIC Network Monitoring Report”, available at
http://www.slac.stanford.edu/xorg/icfa/icfa-net-paper-jan07/
xlv
Brockwell P. and Davis R, “Introduction to Time Series and Forecasting”, Springer New York, 1996
xlvi
NIST, “e-handbook of statistics”, available at http://www.itl.nist.gov/div898/handbook.
xlvii
Box, George and Jenkins, Gwilym (1970) Time series analysis: Forecasting and control, San
Francisco: Holden-Day
xlviii
R. L.Cottrell, C. Logg, M. Chhaparia, M. Grigoriev, F. Haro, F. Nazir, M. Sandford, “Evaluation of
Techniques to Detect Significant Network Performance Problems using End-t-end Active Network
measurements”, NOMS, April 2006.
xlix
Saqib, F., "Network Weather Forecasting for Management and Analysis of Global Grid and Internet
end-to-end Performance" (BS thesis, National University of Sciences and Technology, Pakistan, 2006).
l
A. Iqbal, Y. T.Li, R. L Cottrell, “Event Diagnosis using Correlation”, ICIMP 07.
li
SLAC/NIIT, “Measurement and Analysis of the Global Grid and Internet End-to-end performance
(MAGGIE)”, available at http://maggie.niit.edu.pk/newwebsite/index.html
lii
J. Navratil, R. L. Cottrell “ABwE: A Practical Aooroach to Available Bandwidth Estimation”, PAM
2003, also available at http://moat.nlanr.net/PAM2003/PAM2003papers/3781.pdf
liii
ICFA/SCIC, “ICFA-SCIC Working Group on Monitoring”, available at
http://www.slac.stanford.edu/xorg/icfa/scic-netmon/.
liv
SLAC, “PingER Case Studies”, available at https://confluence.slac.stanford.edu/display/IEPM/PingER
lv
R. L. Cottrell, S. Khan, “Quantitative Measurements of the Digital Divide”, available at
http://www.slac.stanford.edu/grp/scs/net/talk07/aps-apr07.ppt.
lvi
R. L. Cottrell, “Lessons Learned Monitoring”, available at
http://www.slac.stanford.edu/grp/scs/net/talk07/lessons.ppt.
lvii
R. L. Cottrell, S, Khan, “Quantifyintg the Need for Improved Network Performance for South Asia”,
available at http://www.slac.stanford.edu/grp/scs/net/talk07/sasia-case-apr07.ppt.
lviii
R. L. Cottrell, , A. Rehmatullah, J. Williams and A. Mehdi, “Quanifying the Digital Divide from an
Internet Point of View”, available at http://www.slac.stanford.edu/grp/scs/net/talk06/digital-divideoct06.ppt.
lix
A. Rehmatullah, R. L. Cottrell and J. Williams, “Quantifying the Digital Divide: A Scientific Overview
of the Connectivity of South Asian and African Coountries”, available at
http://www.slac.stanford.edu/grp/scs/net/papers/chep06/paper-final.pdf.
lx
R. L. Cottrell, U. Kalim, S. Khan, and A. Mehdi, “Visualizing the Digital Divide from an Internet Point
of View and Some Challenges”, available at http://www.slac.stanford.edu/grp/scs/net/talk07/comsatsmar07.ppt.
xxxvii
23
R. L. Cottrell, A. Rehmatullah, J. Williams and A. Mehdi, “Internet Monitoring and Results for the
Digital Divide”, available at http://www.slac.stanford.edu/grp/scs/net/talk06/digital-divide-romaniaoct06.ppt
lxii
NCP, “Network Centre for Physics”, available at http://www.ncp.edu.pk/.
lxiii
NIIT, “The Centre for High Performance Scientific Computing at NIIT”, available at
http://www.ncp.edu.pk/
lxiv
Wikipedia, “Simple Network Management Protocol”, available at
http://en.wikipedia.org/wiki/Simple_Network_Management_Protocol.
lxv
Internet2, “Bandwidth Test Controller (BWCTL)”, available at http://e2epi.internet2.edu/bwctl/
lxvi
Internet2, “One-way Ping (OWAMP)”, available at http://e2epi.internet2.edu/owamp/.
lxvii
“DNS.NET homepage”, available at http://www.dns.net/.
lxviii
Internet2, “Shibboleth”, available at http://shibboleth.internet2.edu/.
lxix
GEANT2, “eduGAIN2 interconnecting established AA infrastructures”, available at
http://www.fsknet.dk/text/pdf/04_eduGAIN_GNOMIS-Presentation.pdf
lxx
Wikipedia, “Security Access Markup Language”, available at http://en.wikipedia.org/wiki/SAML.
lxxi
Micronet, “Welcome to Micronet Broadband (Pvt.) Ltd.”, available at http://www.dsl.net.pk/.
lxxii
At the University of Delaware’s Computer Science department, the Distributed Computing Course
(CISC879) has covered efficient exchange of network performance information for distributed computing
extensively, using perfSONAR as a case study.
lxi
24