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Current Text of Report
Terapaths: A QoS Collaborative Data Sharing Infrastructure for Petascale Computing Research: DWMI: Datagrid Wide Area Monitoring Infrastructure
Les Cottrell, Yee-Ting Li & Connie Logg, Stanford Linear Accelerator Laboratory (SLAC)
Summary:
The main goal of the DWMI project is to build, deploy and effectively learn how to use an initially relatively small but rich, robust, sustainable, manageable network monitoring infrastructure focused on the needs of critical HEP experiments such as Atlas, BaBar, CMS, CDF and D0.
Today's data intensive sciences, such as High Energy Physics (HEP), need to share large amounts of data at high speeds. This in turn requires high-performance, reliable end-to-end network paths between the major collaborating sites. In addition network administrators need alerts when there are anomalous events, and grid middleware and end-users need long and short-term forecasting for application and network performance for planning, setting expectations and trouble-shooting. To enable this requires a network monitoring infrastructure between the major sites that can help notify and identify potential problems.
Active monitoring: We have developed an active network monitoring toolkit (IEPM-BW). It provides measurements, data archiving, analysis, reporting and visualization. This is now being used to make regular measurements from the following major LHC related sites: CERN, BNL, Caltech, FNAL, SLAC, and Taiwan. We also have about 60 locations worldwide that are being monitored from these important sites. We use a selection of probes based on the quality and interest in the path being measured utilizing metrics such as network routes, round trip time, one-way delays, available bandwidth and achievable throughput. We are extending the presentation of IEPM-BW by working with the USATLAS and ULTRALIGHT groups to customize reports on their most relevant interests.
To aid the detection of incorrect host settings, we have also implemented features to query the configurations of the network monitoring hosts.
As part of this we have developed and put into production, management tools for automation and robustness, including: installation and update kits; measurement and reporting of unreachable participating hosts; in-depth documentation; and a database of site, host, location, contact, OS, cpu, test parameters With regards to cross-domain end-to-end MPLS circuits using both ESnet and Terapaths technologies, we are currently developing mechanisms to automatically schedule active measurements using IEPM-BW to compare the performance of complete end-to-end QoS paths against normal production services.
Passive Monitoring: We have studied and reported on limitations using current active end-to-end network measurement techniques in future high-speed networks. As a result of this we are exploring the effectiveness of using passive (e.g. Netflow) tools to augment or even replace some of the active measurements. In conjunction with BNL we are building a netflow monitoring toolkit using open source software to bring together quality tools to gather, store, process, analyze and visualize the performance information. The intent is to make this generally available and deploy at LHC sites such as BNL, CERN, SLAC and Michigan.
In fact, much of our development is steared being steered by the requirements of the BNL site, specifically for the Terapaths project, where we have a development version of the entire suite running collecting real netflow data from production network systems.
Event Detection and Diagnosis: It is With the expansion of network infrastructure and the increased networked applications in use, it is becoming increasingly impossible for network managers to manually review thousands the large number of reports each morning to detect, and more importantly diagnose problems. Thus, we are developing tools to automate this activity . This includes by forecasting and comparing the observed with the forecast to detect anomalous events, reporting the events. We are currently field testing the Plateau, and automatically gathering information relevant to the event to assist in diagnosis. One version of the event detection is in production useHolt-Winters and KS algorithms on production networks via IEPM-BW. As part of this, in the last year, we have also detected, reported (together with in-depth case studies) and helped diagnose major problems at sites such as BNL, Taiwan, SDSC, NRL, BINP, and CERN. The code is still in development, we are field testing the alerts to known problems, carefully reviewing the symptoms etc. and working with network providers to understand and see what is needed to diagnose them
We are also in the process of building a framework from which these network alerts can be used to automatically diagnose and identify the cause of network problems. Utilizing hieristics analysis and an innovative scoring system to pin-point the cause of an event we are actively working closely with network providers to field testing the code to review and corroborate the symptoms and problems.
High speed data transport: Our world-leaderhip leadership role in evaluating TCP transport algorithms in production networks led Microsoft to request our help in evaluating their next generation TCP stack (CTCP). Given the extent of Windows deployment it is critical to ensure that CTCP performs well without a negative impact upon the iIternet Internet community.
As part of this we have identified and aided the testing of numerous added features to aid the performance of the delay-based congestion control algorithm used in CTCP. Having finalized our initial report into the deployment impact of using CTCP in production environments on both long and short distance high speed Internet paths, we are know looking to publish currently working on a joint conference paper with Microsoft of our work.
Internet Measurement Confederation: An important aspect of being able to both understand and diagnose network performance problems is the unification of reporting formats and the understanding of tool performance on the Internet.
SLAC has recently started close collaboration with both Internet2 and ESnet to help develop and expand the functionalities of the international PerfSONAR collaboration.
Having had gained much momentum over the last few months due to its open-source, open-community, open-standards based ethos of network monitoring, SLAC were are delighted to help contribute our network analysis skills expertise and experience to apply the PerfSONAR technology to production systems like that of the LHC project.
We aim to apply much of our existing analysis frameworks and tools to benefit the PerfSONAR project - including that of event detection , event diagnosis. and event diagnosis.
For further information on this subject contact:
Dr. Thomas Ndousse,
Mathematical, Information, and Computational Sciences Division
Office of Advanced Scientific Computing Research
Phone: 301-903-9960
tndousse@er.doe.gov