1 / 30

Advanced Computer Networks cs538, Fall 2014 @ UIUC

Advanced Computer Networks cs538, Fall 2014 @ UIUC. Klara Nahrstedt Lecture 8, September 18, 2014 Based on Zheng Wang and Jon Crowcroft , “ QoS Routing for Supporting Multimedia Applications”, IEEE JSAC 1996. Announcements. Next Reading for Thursday, September 26:

mcmanus
Download Presentation

Advanced Computer Networks cs538, Fall 2014 @ UIUC

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. Advanced Computer Networkscs538, Fall 2014 @ UIUC Klara Nahrstedt Lecture 8, September 18, 2014 Based on Zheng Wang and Jon Crowcroft, “QoS Routing for Supporting Multimedia Applications”, IEEE JSAC 1996

  2. Announcements • Next Reading for Thursday, September 26: • X. Yang, D. Clark, A. Berger, “NIRA: A New Inter-Domain Routing Architecture”, IEEE/ACM Transactions on Networking, Vol. 15, No. 4, August 2007 • Proposals for Final Projects • Prepare project proposal • At most 1 page describing • Problem description • Steps you plan to take to address the problem • Related work (at least 3 full academic papers citations) and why your proposed problem is different than those or why your proposed solution is better. • Deadline for proposal: 11:59pm Tuesday, September 23, 2014 • No CLASS on Tuesday, September 23, 2014 • Submit project proposal via email to instructor: klara@Illinois.edu (with subject: cs538 – Final Project Proposal)

  3. Outline • QoS Concept • Single Mixed Metric • Multiple Metrics • Bandwidth and Delay QoS Routing Problem • Path Computation Algorithms • Source Routing Algorithms • Hob-by-Hop Routing Algorithms

  4. Window of Resources Insufficient - Sufficient But scarce Interactive HDTV-quality multi-view video Sufficient To abundant HDTV Requirements Sufficient but Scarce to Sufficient High-quality Audio sufficient insufficient insufficient Sufficient Network File access Sufficient But scarce insufficient abundant 1980 1990 2000 2010 2020 abundant Hardware support CS 414 - Spring 2011

  5. Quality of Service (How to parameterize services?) • To manage resources, we need services over resources • to schedule AV data, to shape access for AV data, to process AV data, to move AV data, etc. • Multimedia systems consist of set of AV-specific services • Processing (media-related) services: retrieve audio/video, record video/audio, compress audio/video, fast forward video, rewind video • Transport (network) services: Stream video, fast forward video, rewind video • To provide multimedia services, services get parameterized with quality levels called Quality of Service CS 414 - Spring 2011

  6. Layered Model for QoS Quality of Experience Quality of Service CS 414 - Spring 2011

  7. Application AV QoS Parameters • QoS for Audio service: • Sample rate – 8000 samples/second (8KHz), 44.1 KHz • Sample resolution – 8 bits per sample, 16 bits per sample • QoS for Video service: • Video frame rate – 25 frames per second, 30 frames per second • Frame Period – 40 ms, 30 ms, 25 ms, … • Frame resolution – 320x240 pixels, 640x480 pixels, 1920x1080 pixels, … • Pixel resolution – 24 bits per pixel, 8 bits per pixel • Frame size – 64KB • Compression rate – 8:1 CS 414 - Spring 2014

  8. Network QoS • Bandwidth – Rate of data transfer, Bit Rate • e.g., 1 Gbps (Ethernet throughput) – level 1 • e.g., 100 Mbps (WiFi throughput) – level 2 • e.g., 128 kbps (ISDN throughput) – level 3 • measured in bits per second • Throughput – rate of successful message delivery over communication channel • Measured in packets per second, data packets per time slot, or bits per second • 30 packets per second; 128 kbps, 10 packets per time slot CS 414 - Spring 2014

  9. Network QoS • Connection setup time • time how long it take to connect the sender and receiver • e.g., 50 ms, 10 ms, … • Error Rate • Measures the total number of bits (packets) that were corrupted or incorrectly received compared with the total number of transmitted bits (packets) • Bit Error Rate (BER) – at physical/MAC layer • In fiber optics, bit error rate (BER) is of the order of 10-8 to 10-12. • In satellite networks, BER is of the order 10-7 • Packet Error Rate (PER) – at IP/transport/application layer – also called Packet Loss Rate CS 414 - Spring 2014

  10. Network QoS • Delay • Latency • End-to-end delay in telecommunication • Response time • Round-trip delay in telecommunication • End-to-End Delay • time interval from the time packet is sent from the sender until the time it is received at the receiver (Treceive – Tsend) • e.g., 80 ms, 100 ms, 160 ms CS 414 - Spring 2014

  11. Network QoS • Response Time • Measured as round-trip delay and is the total time required for sender to send a packet and receive an acknowledgement from the receiver. It can be described as sum of network delay and interface delay. • Network delay – composed of transit delay and transmission delay • Transit delay is caused by time needed to send data on a physical connection between sender and receiver • Transmission delay is time needed to transmit packet through network as result of processing delays (e.g., look up routing tables) • Interface delay – incurred between the time a sender is ready to begin sending and the time a network is ready to accept and transmit the data (due to traffic policing and shaping) CS 414 - Spring 2014

  12. Other QoS Parameters • Jitter • Undesired deviation from true periodicity in telecommunication • Also called packet delay variation – important QoS factor in assessment of network performance • Packet jitter – variation in latency as measured in the variability over time of the packet latency across network. CS 414 - Spring 2014

  13. QoS Classes • Guaranteed Service Class • QoS guarantees are provided based on deterministic and statistical QoS parameters • Predictive Service Class • QoS parameter values are estimated and based on the past behavior of the service • Best Effort Service Class • There are no guarantees or only partial guarantees are provided CS 414 - Spring 2011

  14. QoS Classes (cont.) QoS Class determines: (a) reliability of offered QoS, (b) utilization of resources CS 414 - Spring 2011

  15. Deterministic QoS Parameters Single Value: QoS1 – average (QoSave), contractual value, threshold value, target value Throughput – 10 Mbps Pair Value: <QoS1, QoS2> with QoS1 – required value; QoS2 – desired value <QoSavg,QoSpeak>; <QoSmin, QoSmax> Throughput - <8,12> Mbps CS 414 - Spring 2011

  16. Deterministic QoS Parameter Values • Triple of Values <QoS1, QoS2, QoS3> • QoS1 – best value • QoS2 – average value • QoS3 – worst value • Example: • <QoSpeak, QoSavg, QoSmin>, where QoS is network bandwidth • Throughput <12, 10, 8> Mbps CS 414 - Spring 2011

  17. Guaranteed QoS • We need to provide 100% guarantees for QoS values (hard guarantees) or very close to 100% (soft guarantees) • Current QoS calculation and resource allocation are based on: • Hard upper bounds for imposed workloads • Worst case assumptions about system behavior • Advantages:QoS guarantees are satisfied even in the worst case case (high reliability in guarantees) • Disadvantage: Over-reservation of resources, hence needless rejection of requests CS 414 - Spring 2011

  18. Predictive QoS Parameters • We utilize QoS values (QoS1, ..QoSi) and compute average • QoSbound step at K>i is QoSK = 1/i*∑jQoSj • Weutilize QoS values (QoS1, , QoSi) and compute maximum value • QoSK = max j=1,…i (QoSj) • We utilize QoS values (QoS1, , QoSi) and compute minimum value • QoSK = min j=1,…i (QoSj) CS 414 - Spring 2011

  19. Best Effort QoS • No QoS bounds or possible very weak QoS bounds • Advantages: resource capacities can be statistically multiplexed, hence more processing requests can be granted • Disadvantages: QoS may be temporally violated CS 414 - Spring 2011

  20. Quality-of-Service Routing • Audio/Video Multimedia Applications • Real-time requirement • Throughput requirement • Sustainable performance • Routing: A Key Network Function to Support QoS • Diverse QoS constraints (NP-complete problems) • Best-effort traffic and QoS traffic • Dynamic network state

  21. QoS Routing – Single Metric Bandwidth 50Mbps 30Mbps S 40 Mbps 60 Mbps D 50 Mbps 100 Mbps 50 Mbps 120 Mbps 60 Mbps Minimum Metric b(S,D) = min(b1, b2, b3, …, bn)

  22. QoS Routing – Single Metric Delay 30 ms 40 ms S 50 ms 60 ms D 50 ms 15 ms 100 ms 120 ms 60 ms Additive Metric d (S,D) = d1 + d2 + …. dn

  23. QoS Routing with Single Mixed Metric (50 Mbps, 30 ms, 0.02) (30 Mbps, 35 ms, 0.5) S (40 Mbps, 40 ms, 0.4) D (60 Mbps, 25 ms, 01) (50 Mbps, 30 ms, 0.2) (100 Mbps, 20 ms, 0.01) (50 Mbps, 35 ms, 0.1) (120 Mbp, 15 ms, 0.01) (30 Mbps, 40 ms, 0.2) F(p) = B(P)/ (D(p) x L(p), where B is bandwidth, D is delay, L is loss probability for path p; path with large value is

  24. Multiple Metrics • Problem: Find path subject to multiple constraints • This is NP-complete problem • Simple problem with two constraints is called • “shortest weight-constrained path” • Definition: • d(i,j) be a metric for link (i,j). For any path p = (i,j,….l,m), we say • metric d is additive if d(p) = d(i,j) + d(j,k) +…+ d(l,m). • Metric d is multiplicative if d(p) = d(i,j) x d(j,k) x … x d(l,m) • Metric d is concave if d(p) = min[d(i,j), d(j,k), …, d(l,m)

  25. Path Computation Algorithms – Source Routing – Bandwidth-Delay Routing • Consider directed graph G=(N, A) with N number of nodes (vertices) and A arcs (edges). • (i,j) is arc (edge) • bijbe available bandwidth • dijbe propagation delay • p = (i,j,k,…, l,m) • Bottleneck bandwidth of path is width (p) = min(bij, bjk,…., blm) • Length of path is length (p) = dij + djk + … + dlm • Given any two nodes i and m of the graph and two constraints W and D, the QoS routing problem is then to find a path p* between i and m so that • width (p*) length(p*) • Bandwidth-delay constrained paths

  26. Routing Algorithm (50 Mbps, 30 ms) (60 Mbps, 35 ms) S (40 Mbps, 40 ms) D (60 Mbps, 25 ms) (50 Mbps, 30 ms) (100 Mbps, 20 ms) (50 Mbps, 35 ms) (120 Mbp, 15 ms) (50 Mbps, 40 ms) Constraints: B = 50 Mbps, D = 55ms Step1: find all paths that satisfy B Step 2: find the final path that satisfies D

  27. Hop-by-Hop Routing (50 Mbps, 30 ms) (60 Mbps, 35 ms) S (40 Mbps, 40 ms) D (60 Mbps, 25 ms) (50 Mbps, 30 ms) (100 Mbps, 20 ms) (50 Mbps, 35 ms) (120 Mbp, 15 ms) (50 Mbps, 40 ms) With multiple metrics the best path with all parameters at their optimal values may not exist at all!!!!

  28. Hop-by-Hop Algorithm (1) (50 Mbps, 30 ms) (60 Mbps, 35 ms) S (40 Mbps, 40 ms) D (60 Mbps, 25 ms) (50 Mbps, 30 ms) (100 Mbps, 20 ms) (50 Mbps, 35 ms) (120 Mbp, 15 ms) (50 Mbps, 40 ms) Shortest-widest algorithm with distance vector approach Step 1: find all widest path from node 1 to each node ‘i’. If there are more than one widest path found, Step 2 chooses one with minimum length Step 3 updates the width and length for the shortest-widest path from node 1 to node i (using distance vector approach)

  29. Hop-by-Hop Algorithm (2) (50 Mbps, 30 ms) (60 Mbps, 35 ms) S (40 Mbps, 40 ms) D (60 Mbps, 25 ms) (50 Mbps, 30 ms) (100 Mbps, 20 ms) (50 Mbps, 35 ms) (120 Mbp, 15 ms) (50 Mbps, 40 ms) Shortest-widest algorithm based on link state Step 1: find the nodes with maximum width among the tentatively labeled nodes if there are more than one node found Step 2 chooses one with minimum length and permanently labels Step 3 updates the tentatively labeled nodes around the new permanently labeled node

  30. Conclusion • QoS Routing is integral part of resource management • QoS routing might be integrated with path reservation • Status • QoS has been explored in routers, but not much used • QoS has been used in ATM networks (backbone) • QoS service class concept is now being explored by broadband providers for multimedia services • QoS in wireless challenging and statistical over unlicensed spectrum

More Related