1 / 1

INCITE R. Baraniuk, E. Knightly, R. Nowak, R. Riedi (Rice), L. Cottrell, J. Navratil (SLAC), W. Feng, M. Gardner (LANL)

?. 1. 1. q 4. q 1. q 5. q 6. q 1. q 4. q 2. q 3. q 2. q 3. Technical Challenges. INCITE R. Baraniuk, E. Knightly, R. Nowak, R. Riedi (Rice), L. Cottrell, J. Navratil (SLAC), W. Feng, M. Gardner (LANL).

lexiss
Download Presentation

INCITE R. Baraniuk, E. Knightly, R. Nowak, R. Riedi (Rice), L. Cottrell, J. Navratil (SLAC), W. Feng, M. Gardner (LANL)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. ? 1 1 q4 q1 q5 q6 q1 q4 q2 q3 q2 q3 Technical Challenges INCITER. Baraniuk, E. Knightly, R. Nowak, R. Riedi (Rice), L. Cottrell, J. Navratil (SLAC), W. Feng, M. Gardner (LANL) Edge-based Traffic Processing and Service Inference for High-Performance Networks 7 4 INCITE: InterNet Control and Inference Tools at the Edge PingER/ABwE (SLAC) Network Tomography (Rice, Wisconsin) 1 • Many scientists are unable to participate in science due to poor Internet connectivity • e.g. 10-20% of HENP • collaborators are from • developing nations • To understand need simple, low cost, performance • measurements to and within developing regions providing: Canonical Subproblems: Two senders/receivers problem characterizes network tomography problem in general From edge-based traffic measurements (loss/delay/arrival order), infer internaltopology, link level loss rates, queuing delays • planning, setting expectations, policy setting • PingER meets these needs • < 100bits/s, uses ubiquitous ping • covers > 100 countries (>90% of world’s Internet connected population) 1-by-2 Component 2-by-1 Component • Objectives: • Improve throughput over the Internet for DoE high performance projects • Thrust 1: Traffic analysis and modeling • Thrust 2: Path and tomographic inference • Thrust 3: Data collection tools (PingER, MAGNeT, +) • Approach: • Active and passive network probing • Statistical model based inference Pinger deployment Blue=monitoring site Red=remote site • ABwE tool: abing Characteristics • Interactive (1 – 2 second response) • Low network impact (20 packets/host/direction) • Simple & robust: just need simple responder • installing • Provides measurements in both directions • Provides capacity & available bandwidth • Agrees with more intense/complex methods • Used in MonALISA, IEPM-BW & PlanetLab Common Branch Point: Arrival order usually the same Different Branch Points: arrival order varies depending on delays, offset Arrival order fixed at joining point Arrival Order Based Topology ID ROC Curve Bandwidth Rice LAN Arrival Order and Loss Arrival Order Only 2 Loss Only 1000 probes • Poor understanding of origins of complex network dynamics • Lack of adequate modeling techniques for network dynamics • Internal network inaccessible • Low impact, large scale monitoring • Application-driven traffic modulation • High-speed measurements pathChirp: Efficient Available Bandwidth and Tight Link Estimation (Rice) 5 Chirp: packet train with increasing rate When probe rate exceeds available bandwidth, queuing delay increases The graphs show Abing monitoring dataviaMonALISA 8 Tools: MAGNeT & TICKET (LANL) • MAGNeT: • Monitor for Application-Generated Network Traffic • Monitor traffic immediately after being generated by the application (i.e., unmodulated traffic) and throughout the protocol stack to see how traffic gets modulated. Is TCP/IP the obstacle to high performance? • Create a library of application-generated network traces (not just FTPs) to test network protocols • extend monitoring to kernel events in general 3 Impact and Connections • Impact: • Optimize performance of demanding applications (remote visualization, high- capacity data transfers) • New understanding of the complex dynamics of large-scale, high-speed networks • New edge-based tools to characterize and map network performance as a function of space, time, resource, application, protocol, and service • Highly efficient methods for monitoring in distributed computing systems.  • Connections: Reduce available bandwidth on Gigabit testbed using cross-traffic generator Available bandwidth estimates decrease in proportion to the introduced cross-traffic UIUCRice tight link Locating tight links on two paths sharing 4 common links SLACRice tight link • TICKET: • Traffic Information-Collecting Kernel with Exact Timing • Current solutions to network packet capture (e.g., tcpdump) are too slow or too expensive • Monitor and record traffic at gigabit-per-second (Gb/s) speeds and nanosecond granularity • Price/Performance • Functionally reconfigurable, e.g., real-time intrusion • detection, network flooding, etc. 6 TCP Low-Priority (Rice) • High-speed TCP-LP • TCP-LP + HSTCP [Floyd03] • Linux-2.4.22-web100 • implementation Goal: Utilize excessive bandwidth in a non-intrusive fashion Applications: bulk data transfer, P2P file sharing • Globus • Teragrid • Transpac at Indiana U. • European GridLab Project • San Diego Supercomputing Center • Telcordia • IEPM-BW • Internet2 • ns-2 Simulator • Rice/SLAC/LANL synergy • Particle Physics Data Grid • Collaboratory Pilot (Newman, Cottrell, Mount). • SciDAC Center for Supernova • Research (Warren) • Scientific Workspaces of the • Future (ANL, UIC, LANL, BU, • Brown, NCSA). • TCP alone 745.5 Kb/s • TCP plus 739.5 Kb/sTCP-LP109.5 Kb/ • TCP-LP is invisible to TCP DoE SciDAC high-performance networking research project: INCITE INCITE.rice.edu 2004

More Related