Gong Su Mar. 22, 2000. Columbia University, DCC Lab, March 2000 Multi-Edged Network Applications  Traditional net apps: end-end computing  Client-server.

Slides:



Advertisements
Similar presentations
NetServ Dynamic in-network service deployment Henning Schulzrinne (Columbia University) Srinivasan Seetharaman (Georgia Tech) Volker Hilt (Bell Labs)
Advertisements

AMUSE Autonomic Management of Ubiquitous Systems for e-Health Prof. J. Sventek University of Glasgow In collaboration.
S Licentiate course on Telecommunications Technology (4+1+3 cr.) Course Topic Spring 2000: Routing Algorithms in the DiffServ MPLS Networks Introduction.
Application-Based Network Operations (ABNO) IETF 88 – SDN RG
Security in VoIP Networks Juan C Pelaez Florida Atlantic University Security in VoIP Networks Juan C Pelaez Florida Atlantic University.
UCL VPN Update. 6NET “To look at the issues surrounding the provision of IPv6 dynamic VPN technology and deploy an IPv6- Enabled VPN Infrastructure”
1 InfiniBand HW Architecture InfiniBand Unified Fabric InfiniBand Architecture Router xCA Link Topology Switched Fabric (vs shared bus) 64K nodes per sub-net.
Open Innovation via Java-enabled Network Devices Tal Lavian
RATES: A Server for MPLS Traffic Engineering (Routing And Traffic Engineering Server) Zlatokrilov Haim Advanced Topics in IP Networks5/1/2001 Tel-Aviv.
Polaris Financial Technologies Welcomes the members of Hyderabad chapter for the 2nd event on 4 th July 14 held by PACE (The Testing Practice)
Virtual Active Networks Gong Su Mar. 9, Network Computing Models Traditional: end-to-end, Client-server software at end nodes The network is but.
C OLUMBIA U NIVERSITY Lightwave Research Laboratory Embedding Real-Time Substrate Measurements for Cross-Layer Communications Caroline Lai, Franz Fidler,
1 Integrating a Network IDS into an Open Source Cloud Computing Environment 1st International Workshop on Security and Performance in Emerging Distributed.
Naixue GSU Slide 1 ICVCI’09 Oct. 22, 2009 A Multi-Cloud Computing Scheme for Sharing Computing Resources to Satisfy Local Cloud User Requirements.
(1) Univ. of Rome Tor Vergata, (2) Consortium GARR, (3) CREATE-NET
Use Case for Distributed Data Center in SUPA
TeraPaths: A QoS Collaborative Data Sharing Infrastructure for Petascale Computing Research Bruce Gibbard & Dantong Yu High-Performance Network Research.
1 GAIA VoIP traffic generator and analyzer Presentation by Amrut Bang Ashish Deshpande Vijay Gabale Santosh Patil Sponsored by GS Lab Pvt. Ltd Pune Institute.
PrimoGENI Tutorial Miguel Erazo, Neil Goldman, Nathanael Van Vorst, and Jason Liu Florida International University Other project participants: Julio Ibarra.
Fraunhofer FOKUSCompetence Center NET T. Zseby, CC NET1 IPFIX – IP Flow Information Export Overview Tanja Zseby Fraunhofer FOKUS, Network Research.
Vulnerabilities and Safeguards in Networks with QoS Support Dr. Sonia Fahmy CS Dept., Purdue University.
Remote Access Chapter 4. Learning Objectives Understand implications of IEEE 802.1x and how it is used Understand VPN technology and its uses for securing.
Mobile Networking Challenges1 5.6 Mobile Ad Hoc Networks  Ad hoc network does not have any preexisting centralized server nodes to perform packet routing,
1 Liquid Software Larry Peterson Princeton University John Hartman University of Arizona
Active Network Node in Silicon-Based L3 Gigabit Routing Switch Active Network Node in Silicon-Based L3 Gigabit Routing Switch 1 UC Berkeley Engineering.
Software-defined Networking Capabilities, Needs in GENI for VMLab ( Prasad Calyam; Sudharsan Rajagopalan;
Wireless Access and Terminal Mobility in CORBA Dimple Kaul, Arundhati Kogekar, Stoyan Paunov.
A Virtual Honeypot Framework Author: Niels Provos Published in: CITI Report 03-1 Presenter: Tao Li.
Towards Programmable Virtual Networks John Vicente Columbia University October 5, 1998 Visiting Researcher Intel Corporation O P E N S I G ‘ 9 8 Genesis.
Fast NetServ Data Path: OpenFlow integration Emanuele Maccherani Visitor PhD Student DIEI - University of Perugia, Italy IRT - Columbia University, USA.
Applicazione del paradigma Diffserv per il controllo della QoS in reti IP: aspetti teorici e sperimentali Stefano Salsano Università di Roma “La Sapienza”
S. Dasilva, D. Florissi, Y. Yemini (YY) ++ Distributed Computing & Communications (DCC) Lab Columbia University; D CC.
A Virtual Honeypot Framework Niels Provos Google, Inc. The 13th USENIX Security Symposium, August 9–13, 2004 San Diego, CA Presented by: Sean Mondesire.
Management of the LHCb DAQ Network Guoming Liu * †, Niko Neufeld * * CERN, Switzerland † University of Ferrara, Italy.
1 TCP/IP based TML (Transport Mapping Layer) for ForCES Protocol Hormuzd Khosravi Shuchi Chawla Furquan Ansari Jon Maloy 62 nd IETF Meeting, Minneapolis.
ABone Architecture and Operation ABCd — ABone Control Daemon Server for remote EE management On-demand EE initiation and termination Automatic EE restart.
GRID Overview Internet2 Member Meeting Spring 2003 Sandra Redman Information Technology and Systems Center and Information Technology Research Center National.
This poster has been developed with support from the CATIIS project Program doctoral interregional și transnațional de excelență în domeniile “Calculatoare.
Optical Architecture Invisible Nodes, Elements, Hierarchical, Centrally Controlled, Fairly Static Traditional Provider Services: Invisible, Static Resources,
1 Integrating Active Networking and Commercial-Grade Routing Platforms The University of Maryland Rob Jaeger J.K. Hollingsworth Bobby.
1 | © 2015 Infinera Open SDN in Metro P-OTS Networks Sten Nordell CTO Metro Business Group
1 Java-enable Network Devices Programmable Network Node: Applications 1 Technology Center, Enterprise Solutions, Nortel Networks 2 Department of Computer.
Networking: Applications and Services Antonia Ghiselli, INFN Stu Loken, LBNL Chairs.
Securing the Grid & other Middleware Challenges Ian Foster Mathematics and Computer Science Division Argonne National Laboratory and Department of Computer.
TeraPaths: A QoS Enabled Collaborative Data Sharing Infrastructure for Petascale Computing Research The TeraPaths Project Team Usatlas Tier 2 workshop.
DSN & SensorWare Projects Rockwell Science Center –Charles Chien UCLA –Mani Srivastava, Miodrag Potkonjak USC/ISI –Brian Schott, Bob Parker Virginia Tech.
Management of the LHCb DAQ Network Guoming Liu *†, Niko Neufeld * * CERN, Switzerland † University of Ferrara, Italy.
Spawning Networks COMET Group Columbia University.
1 Revision to DOE proposal Resource Optimization in Hybrid Core Networks with 100G Links Original submission: April 30, 2009 Date: May 4, 2009 PI: Malathi.
Anetd and the Abone SRI International Livio Ricciulli.
Danilo Florissi, Yechiam Yemini (YY), Sushil da Silva, Hao Huang Columbia University, New York, NY 10027
1 Randomized Failover Intrusion Tolerant Systems (RFITS) Ranga Ramanujan Architecture Technology Corporation Odyssey Research Associates DARPA OASIS PI.
Computing Facilities CERN IT Department CH-1211 Geneva 23 Switzerland t CF Cluman: Advanced Cluster Management for Large-scale Infrastructures.
Supporting Advanced Scientific Computing Research Basic Energy Sciences Biological and Environmental Research Fusion Energy Sciences High Energy Physics.
1 Scalability and Accuracy in a Large-Scale Network Emulator Nov. 12, 2003 Byung-Gon Chun.
Software Architecture of Sensors. Hardware - Sensor Nodes Sensing: sensor --a transducer that converts a physical, chemical, or biological parameter into.
1 Dynamic Classification in a Silicon-Based Forwarding Engine Technology Center, Nortel Networks & The University of Maryland Rob Jaeger
Use Case for Distributed Data Center in SUPA
University of Maryland College Park
Potential Areas of Research Activity – March 2000
AERO BGP-Based Routing for Distributed Mobility Management
Virtual Active Networks
GGF15 – Grids and Network Virtualization
Dynamic SFC from Tacker to incept specific traffic of VM
QNX Technology Overview
Virtual Active Networks
Cloud Computing: Concepts
Applying Policy-Based Intrusion Detection to SCADA Networks
Autonomous Network Alerting Systems and Programmable Networks
Integrating Active Networking and Commercial-Grade Routing Platforms
Presentation transcript:

Gong Su Mar. 22, 2000

Columbia University, DCC Lab, March 2000 Multi-Edged Network Applications  Traditional net apps: end-end computing  Client-server software at end nodes  The network is a best-effort packet-transport wire  Active net apps: multi-edge computing  Application components dynamically deployed at net nodes  Examples: intrusion protection, distributed simulation  Need to interact with network resources & topology Traditional netActive nets

Columbia University, DCC Lab, March 2000 VAN Node Architecture  Enables EE to configure net resources & topology  Enables EE to monitor & adapt to net changes Node HW OS EE AA VAN EE AA

Columbia University, DCC Lab, March 2000 VAN: Middleware for Edge-Computing  VAN service architecture  VAN Local Manager (VLM)  Manages local node resources  Monitors & reports resource status  VAN Domain Server (VDS)  VAN provisioning  Resource acquisition  Performance monitoring

Columbia University, DCC Lab, March 2000 VLM and VDS Functions  create/delete VN with desired CPU resource  create/delete VL with desired link resource  modify VN and VL resources  create/delete Virtual Ports (VPs)  bind/unbind VPs to/from VLs  send/receive messages to/from VPs  create/delete a VAN  join/leave a VAN  VLM exports the following services to VDS’es and EE/AAs  VDS export the following services to EE/AAs

Columbia University, DCC Lab, March 2000 Using VAN For Active Fencing  Idea: route suspicious traffic to a protection VAN  Create a VAN that captures traffic from suspicious sources  Deploy active filters to analyze traffic and choke attack  Example: choking denial of service attack using an active fence  Active fencing as a protection paradigm  Dynamic: deploy response filters dynamically  Source-centric: fence the source rather than targets  Globally-coordinated protection

Columbia University, DCC Lab, March 2000 VAN Support of Active Simulation  Problem: partition events flows in large-scale simulation  Event streams tend to cluster dynamically  Events are clustered by meaning, scenario & time scales  Need a way to allocate resources to serve the intensity of a cluster  VAN is used to encapsulate clustered interactions  VAN support cluster interactions:  e.g., VAN of aircraft, VAN of tanks; VAN of a battlefield  Dynamic formation of VAN & dynamic allocation of resources  E.g., allocate more resources to battlefield VAN Aircraft Tank Simulation objects Battlefield

Columbia University, DCC Lab, March 2000 Current Implementation  VAN service APIs  VAN creation/deletion  VN, VP, and VL creation/deletion  VN engine and VL engine loading/unloading and configuration  Monitoring and event handling  Experimental VN Engines and VL Engines  VN engines: traffic redirection, IP routing (RIP capable)  VL engines: plain UDP tunnel, QoS guaranteed (via RSVP) UDP tunnel  Command line front-end tool with scripting capability  VAN MIB instrumentation – monitoring via SNMP

Columbia University, DCC Lab, March 2000 Recent Accomplishments  VAN release 0.1  QoS enabled Virtual Links  Integration with ISI ASP  Integration with UCLA Panda

Columbia University, DCC Lab, March 2000 Near Term Goals: Deployment on ABone  Integration with anetd  Livio Ricciulli at Metanetworks  Adapt vanad to work with anetd  Deployment on ABone  Bob Braden at ISI  Make vanad part of ABone core software

Columbia University, DCC Lab, March 2000 Long Term Goals: Kernel Support & Applications  Kernel resource management support  Scheduler extension  Classifier extension  Virtual link setup (QoS signaling + tunnel encapsulation)  Demo active applications  Active fencing  Others?