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NEXT GENERATION INTERNET PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES Ian F. Akyildiz C. Scoglio, J. de Oliveira, T. Anjali, L. Chen, J. A. Smith*, G. Uhl* and A. Sciuto* 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 IP QoS NETWORK PROJECT (NASA Goddard, Raytheon, Swayles) Challenges – Differentiated Services NASA Ames Research – End-to-End Center QoS – Integrated Services for Multimedia – Network Management IFA'02 Abilene NASA Goddard Space Flight Center BWN Laboratory GATECH NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 2 BWN-Lab Physical Testbed: Experiments and Issues IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 3 BWN-Lab TESTBED Lightstream 1010 ATM 622 Mbps 7505 Gigabit Ethernet Fast Ethernet 7204 VXR ATM 155 Mbps Catalyst 6506 Catalyst 4000 7204 VXR External Lightstream IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 4 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 5 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) IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 6 DiffServ TESTBED NETWORK TOPOLOGY DS domain NASA Abilene marking scheduling policing DS domain shaping BWN-Lab marking DS domain IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 7 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. IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 8 DiffServ EXPERIMENTS SCHEDULING WITH CBWFQ Class Time of Start Requested BW (Mbps) Minimum Guaranteed BW (Mbps) EF (UDP) 0 50 30 AF4 (UDP) 9 40 25 AF1 (UDP) 5 40 20 14 40 None BE (UDP) 60 Bandwidth (Mbps) 50 40 EF AF4 30 AF1 20 BE 10 0 1 3 5 7 9 11 13 15 17 19 Time (sec) We validated CAR and CBWFQ as the policing and scheduling mechanisms for DiffServ implementation IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 9 MPLS TESTBED NETWORK TOPOLOGY Abilene rtr3 7505 Gigabit rtr1 FastEthernet 7200 MPLS Tunnel 1 MPLS Tunnel 2 MPLS Tunnel 3 Gigabit LAN 1 IFA'02 rtr2 7200 Gigabit LAN 2 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 10 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. 50 Bandwidth (Mbps) 45 40 35 TCP1 30 TCP2 25 UDP1 20 UDP2 15 10 5 19 17 15 13 11 9 7 5 3 1 0 Time (sec) IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 11 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 100 90 80 70 UDP1 60 TCP1 50 TCP2 40 UDP2 30 20 10 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 19 17 15 13 11 9 7 5 3 1 0 12 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 100 90 80 70 TCP1 60 TCP2 50 UDP1 40 UDP2 30 20 10 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 19 17 15 13 11 9 7 5 3 1 0 13 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 14 DiffServ-AWARE TE PREEMPTION 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? New Tunnel IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 15 DiffServ-AWARE TE PREEMPTION EXPERIMENTS Cisco’s preemption policy: – Tunnel priority: lowest priority (numerically higher) – Tunnel age: Tunnel created earliest Lowest Priority Tunnel Oldest Tunnel Priority Bandwidth Preempted Priority Bandwidth Preempted Tunnel 1 7 50 50 Tunnel 2 7 30 6 20 Tunnel 3 6 20 1 20 Tunnel 4 1 20 Tunnel 1 7 30 Tunnel 2 7 Tunnel 3 Tunnel 4 IFA'02 Tunnel X NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES X 16 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 17 TEAM/AA Architecture: Managing Multiple Domain DiffServ MPLS Networks Research Contributions and Issues IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 18 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 19 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 LSP Routing Traffic Routing LSP Setup/ Dimensioning DiffServ/MPLS Domain LSP Capacity Allocation LSP Preemption Location Management Handoff Management TEAM IFA'02 Network Planning NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 20 TEAM/AA ARCHITECTURE Inter-domain operation TEAM TEAM TEAM AA AA AA AA AA AA IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 21 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 22 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] IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 23 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 Driven Policy 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. IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 24 OPTIMIZATION PROBLEM Optimal policy * such that Optimality equation where IFA'02 wb ( S , a ) w sw ( S , a ) r ( S , a ) Wsign( S , a ) NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 25 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] IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 26 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 27 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 28 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. IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 29 PERFORMANCE COMPARISON: COMMERCIAL VERSUS ADAPTIVE POLICY Number of Preempted LSPs IFA'02 Bandwidth Wastage Requested bw Mbps Commercial Policy Adaptive Policy Requested bw Mbps Commercial Policy Adaptive Policy 15 1 0 15 10 0 25 1 0 25 0 0 30 2 0 30 70 0 40 2 0 40 60 0 55 2 0 55 45 0 65 2 0 65 35 0 90 2 1 90 10 0 100 2 2 100 0 0 155 6 2 155 16 0 185 7 3 185 71 0 240 7 4 240 16 0 280 8 5 280 1 0 325 10 6 325 66 0 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 30 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] IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 31 RESOURCE MANAGEMENT – LSP BANDWIDTH ALLOCATION A method to determine Bandwidth Allocation for LSPs with less bandwidth wastage and less redimensioning 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 IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 32 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 LSP Routing Traffic Routing LSP Setup/ Dimensioning DiffServ/MPLS Domain LSP Capacity Allocation LSP Preemption Location Management Handoff Management TEAM IFA'02 Network Planning NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 33 TEAM/AA ARCHITECTURE Inter-domain operation TEAM TEAM TEAM AA AA AA AA AA AA IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 34 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. IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 35 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. IFA'02 NGI PHYSICAL TESTBED: RESEARCH AND MANAGEMENT ISSUES 36