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Broadband and Wireless Networking Laboratory School of Electrical and Computer Engineering

Broadband and Wireless Networking Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology, Atlanta, GA, USA. *NASA Goddard Space Flight Center Greenbelt, MD, 20771, USA. Abilene. IP QoS NETWORK PROJECT (NASA Goddard, Raytheon, Swayles). Challenges

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Broadband and Wireless Networking Laboratory School of Electrical and Computer Engineering

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  1. Broadband and Wireless Networking Laboratory School of Electrical and Computer Engineering Georgia Institute of Technology, Atlanta, GA, USA *NASA Goddard Space Flight Center Greenbelt, MD, 20771, USA

  2. Abilene IP QoS NETWORK PROJECT(NASA Goddard, Raytheon, Swayles) • Challenges • Differentiated Services • End-to-End QoS • Integrated Services for Multimedia • Network Management NASA Ames Research Center NASA Goddard Space Flight Center BWN Laboratory GATECH NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  3. BWN-Lab Physical Testbed: Experiments and Issues NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  4. BWN-Lab TESTBED 7204 VXR ATM155 Mbps Gigabit Ethernet Fast Ethernet ATM 622 Mbps 7505 Lightstream 1010 Catalyst 6506 Catalyst4000 7204 VXR ExternalLightstream NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  5. TESTBED HARDWARE • 2 Cisco 7200 routers: • FastEthernet/OC3/GigabitEthernet interfaces • Cisco 7500 router: • GEIP+/OC12 interfaces • Cisco Catalyst 6506 layer 3 switch: • GEIP+ interface • Cisco Catalyst 4000 switch: • FastEthernet ports • Cisco LightStream 1010 switch: • OC3 interfaces NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  6. TESTBED SOFTWARE • Cisco IOS • Version 12.2(1)E1 on the routers • Native IOS on switch 6500 • End-hosts • MS Win ME and Linux RedHat 7.2 • ALTQ 2.2: Scheduling/Queueing Software • Iperf: traffic generation and traffic characteristic measurement • MRTG and MRTG++ (modified MRTG for 10s sampling) NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  7. DiffServ TESTBED NETWORK TOPOLOGY DS domain NASA Abilene marking policing scheduling DS domain shaping marking BWN-Lab DS domain NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  8. DiffServ EXPERIMENTS • EDGE COMPONENTS • Classification/Marking: Policy Based Routing (PBR) allows classifications based on IP Precedence. • Policing: Committed Access Rate (CAR) enforces a specified traffic profile preventing non-conformant traffic from entering the network. • Shaping: Generic Traffic Shaping (GTS) follows the token bucket algorithm. • CORE COMPONENTS • Queueing: Class-Based WFQ (CBWFQ) regulates traffic submitted to the network, which may delay packets to adjust traffic stream characteristics to a defined profile. • Congestion avoidance: Weighted RED (WRED) allows definition of multiple drop probability profiles. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  9. DiffServ EXPERIMENTSSCHEDULING WITH CBWFQ We validated CAR and CBWFQ as the policing and scheduling mechanisms for DiffServ implementation NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  10. MPLS Tunnel 1 MPLS Tunnel 2 MPLS Tunnel 3 MPLS TESTBED NETWORK TOPOLOGY Abilene rtr3 7505 Gigabit FastEthernet rtr1 rtr2 7200 7200 Gigabit Gigabit LAN 2 LAN 1 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  11. MPLS TE EXPERIMENTS • Goal: Evaluate the benefits of MPLS TE • Case Study 1: Traditional IP Network (Min Hop  rtr1-rtr2) • Best-effort service only • Two 40 Mbps UDP flows are sent from rtr1 to rtr2 • Two 100 Mbps TCP flows are sent from rtr1 to rtr2 • All flows take the min-hop path (FastEthernet) and are limited to a total of 100 Mbps. UDP starves the TCP flows. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  12. MPLS TE EXPERIMENTS • Goal: Evaluate the MPLS TE Properties • Case Study 2: MPLS Network – Mixed Flows • 3 MPLS tunnels were set up. • Two 40 Mbps UDP flows sent from rtr1 to rtr2 • Two 100 Mbps TCP flows sent from rtr1 to rtr2 • Tunnel1: UDP1 + TCP1; Tunnel2: TCP2; Tunnel3: UDP2 • TCP1 reduces rate when UDP1 arrives due to BW contention NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  13. MPLS TE EXPERIMENTS • Goal: Evaluate the MPLS TE properties • Case Study 3: MPLS Network – Separate Flows • 3 MPLS tunnels • Two 40Mbps UDP flows sent from rtr1 to rtr2 • Two 100 Mbps TCP flows sent from rtr1 to rtr2 • Tunnel1: TCP1; Tunnel2: TCP2; Tunnel3: UDP1 + UDP2 • No interference between TCP and UDP NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  14. EXPERIMENTAL CONCLUSIONS • The MPLS TE provides better resource utilization and throughput • Cisco’s MPLS tunnels implementation does not enforce the limit on the tunnel reserved bandwidth – needs improvement • CAR policing is not implementable on Tunnel interfaces NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  15. New Tunnel DiffServ-AWARE TEPREEMPTION EXPERIMENTS • Goal: To evaluate Cisco’s preemption policy • 3 MPLS tunnels were setup between routers, sharing a FastEthernet link • Tunnels 1, 2, and 3 together require the total link bandwidth • A new bandwidth request arrives for Tunnel 4, which has higher priority than the other 3 tunnels • One of the previously established tunnels must be preempted. Which one? NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  16. Tunnel Priority Bandwidth Preempted Tunnel 1 7 30 X Tunnel Priority Bandwidth Preempted Tunnel 2 7 50 Tunnel 1 7 50 X Tunnel 3 6 20 Tunnel 2 7 30 Tunnel 4 1 20 Tunnel 3 6 20 Tunnel 4 1 20 DiffServ-AWARE TEPREEMPTION EXPERIMENTS • Cisco’s preemption policy: • Tunnel priority: lowest priority (numerically higher) • Tunnel age: Tunnel created earliest Lowest Priority Oldest Tunnel NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  17. EXPERIMENTAL CONCLUSIONS • DiffServ-aware TE support in Cisco’s IOS is not completely deployed • Preemption is purely based on tunnel priority and age – waste of resources NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  18. TEAM/AA Architecture: Managing Multiple Domain DiffServ MPLS Networks Research Contributions and Issues NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  19. RELATED WORK • RATES (Routing and Traffic Engineering Server) • Software by Bell Labs for MPLS Traffic Engineering (TE) • Uses Common Open Policy Service (COPS) and Minimum Interference Routing Algorithm (MIRA) • It achieves TE by routing of bandwidth guaranteed LSPs • TEQUILA (TE for QoS in the Internet at Large Scale) • European research project for end-to-end QoS in DiffServ network • Components for monitoring, TE, SLS management, and policy management • Algorithms and techniques are not concretely defined yet and their quantitative evaluation has not been carried out • MATE (Multipath Adaptive Traffic Engineering) • Software by Bell Labs for MPLS TE • Assumes LSP layout using a long term traffic matrix. The focus is on load balancing short term traffic fluctuations • Not designed for bandwidth guaranteed services NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  20. TRAFFIC ENGINEERING AUTOMATED MANAGER (TEAM)“Design and Management Tools for an MPLS Domain QoS Manager,” to appear in Proceedings of SPIE ITCOM 2002, Boston, August 2002. Intra-domain operation To Neighboring TEAM To Neighboring Domain Management Plane Route LSP Routing DiffServ/MPLS Domain Traffic Routing LSP Setup/ Dimensioning Resource LSP Capacity Allocation LSP Preemption Location Management Mobility Handoff Management Network Planning TEAM NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  21. AA AA AA AA AA AA TEAM/AAARCHITECTURE Inter-domain operation TEAM TEAM TEAM NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  22. TEAM/AA ARCHITECTURE • Traffic Engineering Automated Manager (TEAM) and Adaptive Agent (AA): • Manage heterogeneous networks • Different services such as best-effort, real-time, etc. • Different network technologies such as wired and wireless mobile networks • Manage large networks • Multiple domains NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  23. TEAM COMPONENTS • Traffic Engineering Tool [5] • Resource Management • Optimal Policy for LSP Setup [1, 2] • Adaptive preemption policy for LSPs [3] • Traffic estimation and resource allocation scheme [4,6] NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  24. RESOURCE MANAGEMENT – LSP SETUP“A New Threshold-Based Policy for Label Switched Path Setup in MPLS Networks,” in proceedings of ITC 2001, Salvador da Bahia, Brazil, pp. 1-11, December 2001.“Optimal Policy for Label Switched Path Setup in MPLS Networks,”accepted for publication in Computer Networks Journal, 2002. Determine an Adaptive Traffic DrivenPolicy for LSP Setup and Dimensioning for each MPLS Network. • Based on Markov Decision Process theory. • Objective Function: • Minimize the expected infinite-horizon discounted total cost. • To determine the optimal policy,  the transition probabilities and the optimality equations • The optimality equations are solved using the Value Iteration Algorithm. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  25. OPTIMIZATION PROBLEM Optimal policy * such that Optimality equation where NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  26. TEAM COMPONENTS • Traffic Engineering Tool [5] • Resource Management • Optimal Policy for LSP Setup [1, 2] • Adaptive Preemption Policy for LSPs [3] • Traffic estimation and resource allocation scheme [4,6] NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  27. RESOURCE MANAGEMENT – LSP PREEMPTION“A New Preemption Policy for DiffServ-Aware Traffic Engineering to Minimize Rerouting,” to appear in Proceedings of IEEE INFOCOM 2002, New York City, June 2002. • Non-real time applications may afford to have their transmission rate reduced. • By reducing the rate in a fair fashion: • These LSPs would not be torn down, • There would be no service disruption, extra setup and tear down signaling • THERE WOULD BE NO REROUTING DECISIONS NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  28. ADAPTIVE PREEMPTION POLICY (Contd.) • Combines the three main preemption criteria: • Priority of preempted LSPs • Number of preempted LSPs • Bandwidth of preempted LSPs • Optimization formulation and heuristic NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  29. ADAPTIVE PREEMPTION POLICY – OPTIMIZATION FORMULATION Minimize: F =  (priority cost) +  (number of LSPs) +  (preempted bandwidth) + BW module cost Subject to: • Number of preempted modules  r • Number of preempted modules in a preempted LSP is equal to total number of modules in the LSP. • Number of preempted modules in a rate reduced LSP is less than  % of the total number of modules in the LSP. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  30. PERFORMANCE COMPARISON:COMMERCIAL VERSUS ADAPTIVE POLICY Number of Preempted LSPs Bandwidth Wastage NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  31. TEAM COMPONENTS • Traffic Engineering Tool [5] • Resource Management • Optimal Policy for LSP Setup [1, 2] • Adaptive Preemption Policy for LSPs [3] • Traffic Estimation and Resource Allocation Scheme [4,6] NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  32. RESOURCE MANAGEMENT –LSP BANDWIDTH ALLOCATION A method to determine Bandwidth Allocation for LSPs with less bandwidth wastage and less re-dimensioning in an MPLS Network. • Simple method is over-provisioning or cushion • New Method  based on Kalman filter for optimal estimation of the traffic and capacity prediction by determining transition probabilities NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  33. TRAFFIC ENGINEERING AUTOMATED MANAGER (TEAM)“Design and Management Tools for an MPLS Domain QoS Manager,” to appear in Proceedings of SPIE ITCOM 2002, Boston, August 2002. Intra-domain operation To Neighboring TEAM To Neighboring Domain Management Plane Route LSP Routing DiffServ/MPLS Domain Traffic Routing LSP Setup/ Dimensioning Resource LSP Capacity Allocation LSP Preemption Location Management Mobility Handoff Management Network Planning TEAM NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  34. AA AA AA AA AA AA TEAM/AAARCHITECTURE Inter-domain operation TEAM TEAM TEAM NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  35. PUBLICATIONS [1] C. Scoglio, T. Anjali, J. de Oliveira, I. Akyildiz, and G. Uhl, “A New Threshold-Based Policy for Label Switched Path Setup in MPLS Networks,” in proceedings of ITC 2001, Salvador da Bahia, Brazil, pp. 1-11, December 2001. [2] T. Anjali, C. Scoglio, J. de Oliveira, I. Akyildiz, and G. Uhl, “Optimal Policy for Label Switched Path Setup in MPLS Networks,” accepted for publication in Computer Networks Journal, 2002. [3] J. de Oliveira, C. Scoglio, I. Akyildiz, and G. Uhl, “A New Preemption Policy for DiffServ-Aware Traffic Engineering to Minimize Rerouting,” to appear in proceedings of IEEE INFOCOM 2002, New York City, June 2002. [4] C. Bruni, C. Scoglio, and S. Vergari, “Optimal Capacity Provisioning for Label Switched Paths in MPLS Networks,” to appear in proceedings of IFIP-TC6 Networking 2002, Pisa, Italy, May 2002. [5] J. de Oliveira, C. Scoglio, T. Anjali, L. Chen, I. Akyildiz, and G. Uhl, “Design and Management Tools for an MPLS Domain QoS Manager,” to appear in Proceedings of SPIE ITCOM 2002, Boston, August 2002. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

  36. PUBLICATIONS (Contd.) [6] T. Anjali, C. Scoglio, I. Akyildiz, and G. Uhl, “A New Scheme for Traffic Estimation and Resource Allocation for Bandwidth Brokers,” submitted for publication, 2002. [7] T. Anjali, C. Scoglio, L. Chen, I. Akyildiz, and G. Uhl, “ABEst: An Available Bandwidth Estimator within an Autonomous System,” submitted for publication, 2002. [8] J. de Oliveira, F. Martinelli, and C. Scoglio, “SPeCRA: A Stochastic Performance Comparison Routing Algorithm for LSP Setup in MPLS Networks,” submitted for publication, 2002. [9] J. L. Marzo, E. Calle, C. Scoglio, and T. Anjali, “Adding QoS Protection in Order to Enhance MPLS QoS Routing,” submitted for publication, 2002. NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES

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