Networking Tutorials

1. Session 1813Traffic Behavior and Queuing in a QoS Environment Networking Tutorials Prof. Dimitri P. Bertsekas Department of Electrical Engineering M.I.T.

2. Objectives • Provide some basic understanding of queuing phenomena • Explain the available solution approaches and associated trade-offs • Give guidelines on how to match applications and solutions

3. Outline • Basic concepts • Source models • Service models (demo) • Single-queue systems • Priority/shared service systems • Networks of queues • Hybrid simulation (demo)

4. Outline • Basic concepts • Performance measures • Solution methodologies • Queuing system concepts • Stability and steady-state • Causes of delay and bottlenecks • Source models • Service models (demo) • Single-queue systems • Priority/shared service systems • Networks of queues • Hybrid simulation (demo)

5. Performance Measures • Delay • Delay variation (jitter) • Packet loss • Efficient sharing of bandwidth • Relative importance depends on traffic type (audio/video, file transfer, interactive) • Challenge: Provide adequate performance for (possibly) heterogeneous traffic

6. Solution Methodologies • Analytical results (formulas) • Pros: Quick answers, insight • Cons: Often inaccurate or inapplicable • Explicit simulation • Pros: Accurate and realistic models, broad applicability • Cons: Can be slow • Hybrid simulation • Intermediate solution approach • Combines advantages and disadvantages of analysis and simulation

7. Examples of Applications

8. Queuing System Concepts: Arrival Rate, Occupancy, Time in the System • Queuing system • Data network where packets arrive, wait in various queues, receive service at various points, and exit after some time • Arrival rate • Long-term number of arrivals per unit time • Occupancy • Number of packets in the system (averaged over a long time) • Time in the system (delay) • Time from packet entry to exit (averaged over many packets)

9. Stability and Steady-State • A single queue system is stable if packet arrival rate < system transmission capacity • For a single queue, the ratio packet arrival rate / system transmission capacity is called the utilization factor • Describes the loading of a queue • In an unstable system packets accumulate in various queues and/or get dropped • For unstable systems with large buffers some packet delays become very large • Flow/admission control may be used to limit the packet arrival rate • Prioritization of flows keeps delays bounded for the important traffic • Stable systems with time-stationary arrival traffic approach a steady-state

10. Little’s Law • For a given arrival rate, the time in the system is proportional to packet occupancy N =  T where N: average # of packets in the system : packet arrival rate (packets per unit time) T: average delay (time in the system) per packet • Examples: • On rainy days, streets and highways are more crowded • Fast food restaurants need a smaller dining room than regular restaurants with the same customer arrival rate • Large buffering together with large arrival rate cause large delays

11. Explanation of Little’s Law • Amusement park analogy: people arrive, spend time at various sites, and leave • They pay $1 per unit time in the park • The rate at which the park earns is $N per unit time (N: average # of people in the park) • The rate at which people pay is $ T per unit time (: traffic arrival rate, T: time per person) • Over a long horizon: Rate of park earnings = Rate of people’s payment or N =  T

12. Delay is Caused by Packet Interference • If arrivals are regular or sufficiently spaced apart, no queuing delay occurs Regular Traffic Irregular but Spaced Apart Traffic

13. Burstiness Causes Interference • Note that the departures are less bursty

14. Burstiness ExampleDifferent Burstiness Levels at Same Packet Rate Source: Fei Xue and S. J. Ben Yoo, UCDavis, “On the Generation and Shaping Self-similar Traffic in Optical Packet-switched Networks”, OPNETWORK 2002

15. Packet Length Variation Causes Interference Regular arrivals, irregular packet lengths

16. High Utilization Exacerbates Interference As the work arrival rate: (packet arrival rate * packet length) increases, the opportunity for interference increases

17. Bottlenecks • Types of bottlenecks • At access points (flow control, prioritization, QoS enforcement needed) • At points within the network core • Isolated (can be analyzed in isolation) • Interrelated (network or chain analysis needed) • Bottlenecks result from overloads caused by: • High load sessions, or • Convergence of sufficient number of moderate load sessions at the same queue

18. Bottlenecks Cause Shaping • The departure traffic from a bottleneck is more regular than the arrival traffic • The inter-departure time between two packets is at least as large as the transmission time of the 2nd packet

19. Bottlenecks Cause Shaping Bottleneck 90% utilization Incoming traffic Outgoing traffic Exponential inter-arrivals gap

20. Incoming traffic Outgoing traffic Bottleneck 90% utilization Small Medium Large

21. Packet Trains Inter-departure times for small packets

22. Variable packet sizes Peaks smeared Histogram of inter-departure times for small packets # of packets Variable packet sizes Constant packet sizes sec

23. Outline • Basic concepts • Source models • Poisson traffic • Batch arrivals • Example applications – voice, video, file transfer • Service models (demo) • Single-queue systems • Priority/shared service systems • Networks of queues • Hybrid simulation (demo)

24. Poisson Process with Rate l • Interarrival times are independent and exponentially distributed • Models well the accumulated traffic of many independent sources • The average interarrival time is 1/ l (secs/packet), so l is the arrival rate (packets/sec)

25. Batch Arrivals • Some sources transmit in packet bursts • May be better modeled by a batch arrival process (e.g., bursts of packets arriving according to a Poisson process) • The case for a batch model is weaker at queues after the first, because of shaping

26. State 0 State 1 OFF ON Markov Modulated Rate Process (MMRP) • Extension: Models with more than two states Stay in each state an exponentially distributed time, Transmit according to different model (e.g., Poisson, deterministic, etc) at each state

27. Source Types • Voice sources • Video sources • File transfers • Web traffic • Interactive traffic • Different application types have different QoS requirements, e.g., delay, jitter, loss, throughput, etc.

28. Source Type Properties

29. Typical Voice Source Behavior

30. MPEG1 Video Source Model • The MPEG1 MMRP model can be extremely bursty, and has “long range dependency” behavior due to the deterministic frame sequence Diagram Source: Mark W. Garrett and Walter Willinger, “Analysis, Modeling, and Generation of Self-Similar VBR Video Traffic, BELLCORE, 1994

31. Outline • Basic concepts • Source models • Service models • Single vs. multiple-servers • FIFO, priority, and shared servers • Demo • Single-queue systems • Priority/shared service systems • Networks of queues • Hybrid simulation (demo)

32. Device Queuing Mechanisms • Common queue examples for IP routers • FIFO: First In First Out • PQ: Priority Queuing • WFQ: Weighted Fair Queuing • Combinations of the above • Service types from a queuing theory standpoint • Single server (one queue - one transmission line) • Multiple server (one queue - several transmission lines) • Priority server (several queues with hard priorities - one transmission line) • Shared server (several queues with soft priorities - one transmission line)

33. Single Server FIFO • Single transmission line serving packets on a FIFO (First-In-First-Out) basis • Each packet must wait for all packets found in the system to complete transmission, before starting transmission • Departure Time = Arrival Time + Workload Found in the System + Transmission time • Packets arriving to a full buffer are dropped

34. FIFO Queue • Packets are placed on outbound link to egress device in FIFO order • Device (router, switch) multiplexes different flows arriving on various ingress ports onto an output buffer forming a FIFO queue

35. Multiple Servers • Multiple packets are transmitted simultaneously on multiple lines/servers • Head of the line service: packets wait in a FIFO queue, and when a server becomes free, the first packet goes into service

36. Priority Servers • Packets form priority classes (each may have several flows) • There is a separate FIFO queue for each priority class • Packets of lower priority start transmission only if no higher priority packet is waiting • Priority types: • Non-preemptive (high priority packet must wait for a lower priority packet found under transmission upon arrival) • Preemptive (high priority packet does not have to wait …)

37. Priority Queuing • Packets are classified into separate queues • E.g., based on source/destination IP address, source/destination TCP port, etc. • All packets in a higher priority queue are served before a lower priority queue is served • Typically in routers, if a higher priority packet arrives while a lower priority packet is being transmitted, it waits until the lower priority packet completes

38. Shared Servers • Again we have multiple classes/queues, but they are served with a “soft” priority scheme • Round-robin • Weighted fair queuing

39. Round-Robin/Cyclic Service • Round-robin serves each queue in sequence • A queue that is empty is skipped • Each queue when served may have limited service (at most k packets transmitted with k = 1 or k > 1) • Round-robin is fair for all queues (as long as some queues do not have longer packets than others) • Round-robin cannot be used to enforce bandwidth allocation among the queues.

40. Fair Queuing • This scheduling method is inspired by the “most fair” of methods: • Transmit one bit from each queue in cyclic order (bit-by-bit round robin) • Skip queues that are empty • To approximate the bit-by-bit processing behavior, for each packet • We calculate upon arrival its “finish time under bit-by-bit round robin” assuming all other queues are continuously busy, and we transmit by FIFO within each queue • Transmit next the packet with the minimum finish time • Important properties: • Priority is given to short packets • Equal bandwidth is allocated to all queues that are continuously busy

41. Weighted Fair Queuing • Fair queuing cannot be used to implement bandwidth allocation and soft priorities • Weighted fair queuing is a variation that corrects this deficiency • Let wk be the weight of the kth queue • Think of round-robin with queue k transmitting wk bits upon its turn • If all queues have always something to send, the kth queue receives bandwidth equal to a fraction wk / Si wi of the total bandwidth • Fair queuing corresponds to wk = 1 • Priority queuing corresponds to the weights being very high as we move to higher priorities • Again, to deal with the segmentation problem, we approximate as follows: For each packet: • We calculate its “finish time” (under the weighted bit-by-bit round robin scheme) • We next transmit the packet with the minimum finish time

42. Weighted Fair Queuing Illustration Weights: Queue 1 = 3 Queue 2 = 1 Queue 3 = 1

43. Combination of Several Queuing Schemes • Example – voice (PQ), guaranteed b/w (WFQ), Best Effort (Cisco’s LLQ implementation)

44. Demo: FIFO FIFO Bottleneck 90% utilization

45. Demo: FIFO Queuing Delay Applications have different requirements • Video • delay, jitter • FTP • packet loss Control beyond “best effort” needed • Priority Queuing (PQ) • Weighted Fair Queuing (WFQ)

46. Demo: Priority Queuing (PQ) PQ Bottleneck 90% utilization

47. Demo: PQ Queuing Delays PQ FTP FIFO PQ Video

48. Demo: Weighted Fair Queuing (WFQ) WFQ Bottleneck 90% utilization

49. Demo: WFQ Queuing Delays PQ FTP WFQ FTP FIFO WFQ/PQ Video

50. Queuing: Take Away Points • Choice of queuing mechanism can have a profound effect on performance • To achieve desired service differentiation, appropriate queuing mechanisms can be used • Complex queuing mechanisms may require simulation techniques to analyze behavior • Improper configuration (e.g., queuing mechanism selection or weights) may impact performance of low priority traffic