CIS 203

1. CIS 203 05 : Congestion and Performance Issues

2. High-Speed LANs • Speed and power of personal computers has increased • LAN viable and essential computing platform • Client/server computing dominant architecture • Web-focused intranet • Frequent transfer of potentially large volumes of data in a transaction-oriented environment • 10-Mbps Ethernet and 16-Mbps token ring not up to job

3. Uses of High-Speed LANs • Centralized server farms • Client systems draw huge amounts of data from multiple centralized servers • E.g. color publishing • Servers hold tens of gigabytes of image data that must be downloaded to workstations • Power workgroups • Small number of users drawing data across network • E.g.s Software development group, computer-aided design (CAD) • High-speed local backbone • LANs proliferate at a site, • High-speed interconnection is necessary

4. Corporate Wide Area Networking Needs • Up to 1990s, centralized data processing model • Dispersed employees into multiple smaller offices • Growing use of telecommuting • Application structure changed • Client/server and intranet computing • More reliance on PCs, workstations, and servers • GUIs gives user graphic applications, multimedia etc. • Internet access • A few mouse clicks can trigger huge volumes of data • Traffic patterns unpredictable • Average load has risen • More data transported off premises • Traditionally 80% traffic local 20% wide area • No longer applies • Greater burden on LAN backbones and on WAN

5. Digital Electronics Examples • Digital Versatile Disk (DVD) • Huge storage capacity and vivid quality • Digital camcorder • Easy for individuals and companies to make digital video files and place on Web sites •  Digital Still Camera • Individual personal pictures • Companies online product catalogs with full-color pictures of every product

6. QoS on The Internet • IP designed to provide best-effort, fair delivery service • All packets treated equally • As traffic grows, congestion occurs, all packet delivery slowed • Packets dropped at random to ease congestion • Only networking scheme designed to support both traditional TCP and UDP and real-time traffic is ATM • Means constructing second infrastructure for real-time traffic or replacing existing IP-based configuration with ATM • Two types of traffic • Elastic traffic can adjust, over wide ranges, to changes in delay and throughput • Supported on TCP/IP • Handle congestion by reducing rate data presented to network

7. Elastic Traffic • File transfer, electronic mail, remote logon, network management, Web access • E-mail insensitive to changes in delay • User expects file transfer delay proportional to file size and so is sensitive to changes in throughput • With network management, delay is not concern • If failures cause congestion, network management messages must get through minimum delay • Interactive applications, (remote logon, Web access) quite sensitive to delay  • Even for elastic traffic QoS-based service could help

8. Inelastic Traffic • Inelastic traffic does not easily adapt, if at all, to changes in delay and throughput • E.g. real-time traffic • Voice and video • Requirements  • Throughput: minimum value may be required • Delay: e.g. stock trading • Delay variation: Larger variation needs larger buffers • Packet loss: Applications vary in packet loss that they can sustain • Difficult to meet with variable queuing delays and congestion losses • Need preferential treatment to some applications • Applications need to be able to state requirements

9. Supporting Both • When supporting inelastic traffic, elastic traffic must still be supported • Inelastic applications do not back off in the face of congestion • TCP-based applications do • When congested, inelastic traffic continues high load, • Elastic traffic crowded off • Reservation protocol can help • Deny requests that would leave too few resources available to handle current elastic traffic

10. Figure 5.1 Application Delay Sensitivity and Criticality

11. Performance Requirements Response Time • Time it takes a system to react to a given input • Time between last keystroke and beginning of display of result • Time it takes for system to respond to request • Quicker response imposes greater cost • Computer processing power • Competing requirements • Providing rapid response to some processes may penalize others • User response time • Between user receiving complete reply and enters next command (think time) • System response time • Between user entering command and complete response 

12. Figure 5.2 Response Time Results for High-Function Graphics

13. Figure 5.3 Response Time Requirements

14. Throughput • Higher transmission speed makes possible increased support for different services • e.g., Integrated Services Digital Network [ISDN] and broadband-based multimedia services • Need to know demands each service puts on storage and communications of systems • Services grouped into data, audio, image, and video

15. Figure 5.4 Required Data Rates for Various Information Types

16. Figure 5.5Effective Throughput

17. Performance Metrics • Throughput, or capacity • Data rate in bits per second (bps) • Affected by multiplexing • Effective capacity reduced by protocol overhead • Header bits: TCP and IPv4 at least 40 bytes • Control overhead: e.g. acknowledgements  • Delay • Average time for block of data to go from system to system • Round-trip delay • Getting data from one system to another plus delay acknowledgement   • Transmission delay: Time for transmitter to send all bits of packet • Propagation delay: Time for one bit to transit from source to destination • Processing delay: Time required to process packet at source prior to sending, at any intermediate router or switch, and at destination prior to delivering to application • Queuing delay: Time spend waiting in queues

18. Example Effect of Different Types of Delay – 64kbps • Ignore any processing or queuing delays • 1-megabit file across USA (4800km) • Fiber optic link • Propagation rate speed of light (approximately 3  108 m/s) • Propagation delay (4800103)/(3108) = 0.016 s • In that time host transmits (64  103)(0.016) = 1024 bits • Transmission delay (106)/(64  103) = 15.625 s • Time to transmit file is Transmission delay plus propagation delay =15.641 s • Transmission delay dominates propagation delay • Higher-speed channel would reduce time required

19. Example Effect of Different Types of Delay – 1 Gbps • Propagation delay is still the same • Note this as it is often forgotten! • Transmission delay (106)/(106  103)= 0.001 s • Total time to transmit file 0.017 s • Propagation delay dominates • Increasing data rate will not noticeably speed up delivery of file • Preceding example depends on data rate, distance, propagation velocity, and size of packet • These parameters combined into single critical system parameter, commonly denoted a

20. a (1) • where • R = data rate, or capacity, of the link • L = number of bits in a packet • d = distance between source and destination • v = velocity of propagation of the signal • D = propagation delay

21. a (2) • Looking at the final fraction, can also be expressed: • For fixed packet length, a dependent on R  D product • 64-kbps link, a = 1.024  10–3 • 1-Gbps link, a = 16

22. Impact of a • Send sequence of packets and wait for acknowledgment to each packet before sending next • Stop-and-wait protocol • Transmission time normalized to 1: propagation time is a • a > 1 • Link's bit length greater than that of packet • Assume ACK packet is small enough to ignore its transmission time • t = 0, Station A begins transmitting packet • t = 1, A completes transmission • t = a, leading edge of packet reaches B • t = 1 + a, B has received entire packet • Immediately transmits small acknowledgment packet • T = 1 + 2a, acknowledgment arrives at A • Total elapsed time is 1 + 2a • Hence normalized rate packets can be transmitted is 1/(1 + 2a) • Same result with a < 1

23. Figure 5.6 Effect of a on Link Utilization

24. Throughput as Function of a • For a > 1 stop-and-wait inefficient • Gigabit WANs even for large packets (e.g., 1 Mb), channel is seriously underutilized

25. Figure 5.7 Normalized Throughput as a Function of a for Stop-and-Wait

26. Improving Performance • If lots of users each use small portion of capacity, then for each user, effective capacity is considerably smaller, reducing a • Each user has smaller data rate • May be inadequate • If application uses channel with high a, performance can be improved by allowing application to treat channel as pipeline • Continuous flow of packets • Not waiting for acknowledgment to individual packet • Problems: • Flow control • Error control • Congestion control

27. Flow control • B may need to temporarily restrict flow of packets • Buffer is filling up or application is temporarily busy • By the time signal from B arrives at A, many additional packets in the pipeline • If B cannot absorb these packets, they must be discarded

28. Error control • If B detects error it may request retransmission • If B unable to store incoming packets out of order, A must retransmit packet in error and all subsequent packets • Selective retransmission v. Go-Back-N

29. Congestion control • Various methods by which A can learn there is congestion • A should reduce the flow of packets • Large value of a • Many packets in pipeline between onset of congestion and when A learns about it

30. Queuing Delays • Often queuing delays are dominant • Grow dramatically as system approaches capacity • In shared facility (e.g., network, transmission line, time-sharing system, road network, checkout lines, …) performance typically responds exponentially to increased demand • Figure 5.8 representative example • Upper line shows user response time on shared facility as load increases • Load expressed as fraction of capacity • Lower line is simple projection based on knowledge of system behavior up to load of 0.5 • Note performance will in fact collapse beyond about 0.8 to 0.9

31. Figure 5.8 Projected Versus Actual Response Time

32. What Is Congestion? • Congestion occurs when the number of packets being transmitted through the network approaches the packet handling capacity of the network • Congestion control aims to keep number of packets below level at which performance falls off dramatically • Data network is a network of queues • Generally 80% utilization is critical • Finite queues mean data may be lost

33. Figure 5.9 Input and Output Queues at Node

34. Effects of Congestion • Packets arriving are stored at input buffers • Routing decision made • Packet moves to output buffer • Packets queued for output transmitted as fast as possible • Statistical time division multiplexing • If packets arrive to fast to be routed, or to be output, buffers will fill • Can discard packets • Can use flow control • Can propagate congestion through network

35. Figure 5.10 Interaction of Queues in a Data Network

36. Figure 5.11Ideal NetworkUtilization

37. Practical Performance • Ideal assumes infinite buffers and no overhead • Buffers are finite • Overheads occur in exchanging congestion control messages

38. Figure 5.12The Effects of Congestion

39. Figure 5.13 Mechanisms for Congestion Control

40. Backpressure • If node becomes congested it can slow down or halt flow of packets from other nodes • May mean that other nodes have to apply control on incoming packet rates • Propagates back to source • Can restrict to logical connections generating most traffic • Used in connection oriented that allow hop by hop congestion control (e.g. X.25) • Not used in ATM nor frame relay • Only recently developed for IP

41. Choke Packet • Control packet • Generated at congested node • Sent to source node • e.g. ICMP source quench • From router or destination • Source cuts back until no more source quench message • Sent for every discarded packet, or anticipated • Rather crude mechanism

42. Implicit Congestion Signaling • Transmission delay may increase with congestion • Packet may be discarded • Source can detect these as implicit indications of congestion • Useful on connectionless (datagram) networks • e.g. IP based • (TCP includes congestion and flow control - see chapter 17) • Used in frame relay LAPF

43. Explicit Congestion Signaling • Network alerts end systems of increasing congestion • End systems take steps to reduce offered load • Backwards • Congestion avoidance in opposite direction to packet required • Forwards • Congestion avoidance in same direction as packet required

44. Categories of Explicit Signaling • Binary • A bit set in a packet indicates congestion • Credit based • Indicates how many packets source may send • Common for end to end flow control • Rate based • Supply explicit data rate limit • e.g. ATM

45. Traffic Management • Fairness • Quality of service • May want different treatment for different connections • Reservations • e.g. ATM • Traffic contract between user and network

46. Flow Control • Limits amount or rate of data sent • Reasons: • Source may send PDUs faster than destination can process headers • Higher-level protocol user at destination may be slow in retrieving data • Destination may need to limit incoming flow to match outgoing flow for retransmission

47. Flow Control at Multiple Protocol Layers • X.25 virtual circuits (level 3) multiplexed over data link using LAPB (X.25 level 2) • Multiple TCP connections over HDLC link • Flow control at higher level applied to each logical connection independently • Flow control at lower level applied to total traffic

48. Figure 5.14 Flow Control at Multiple Protocol Layers

49. Flow Control Scope • Hop Scope • Between intermediate systems that are directly connected • Network interface • Between end system and network • Entry-to-exit • Between entry to network and exit from network • End-to-end • Between end user systems

50. Figure 5.15Flow Control Scope