1. DATA COMMUNICATIONS  Telecommunication: communication at a distance.  Data: information presented in whatever form is agreed upon by the parties creating and using the data.  Data communications: the exchange of data between two devices via some form of transmission medium such as a wire cable.

2.  Four fundamental characteristics: 1. Delivery: correct destination 2. Accuracy: correct data 3. Timeliness: fast enough 4. Jitter: uneven delay 1-1 DATA COMMUNICATIONS

3. Figure 1.1 Five components of data communication Components

4. Data Representation  Text Email, articles, etc Coding (Unicode, ASCII)  Numbers Direct conversion  Images Pixels, resolution, gray scale, RGB, YCM  Audio Continuous, signal conversion  Video Movie, continuous/discrete

5. Figure 1.2 Data flow (simplex, half-duplex, and full-duplex) Data Flow (Transmission Modes)

6. NETWORKS A network is a set of devices (often referred to as nodes) connected by communication links.

7. Figure 1.3 Types of connections: point-to-point and multipoint Type of Connections (line configurations)

8. Figure 1.4 Categories of physical topology Physical topology

9. Mesh Figure 1.5 A fully connected mesh topology (five devices) 1 2 3 4 5

10. Star Figure 1.6 A star topology connecting four stations

11. Bus Figure 1.7 A bus topology connecting three stations

12. Ring Figure 1.8 A ring topology connecting six stations

13. Network models  Local area network (LAN)  Wide area network (WAN)  Metropolitan area networks

14. Figure 1.12 A heterogeneous network made of four WANs and two LANs

15. THE INTERNET  History of the Internet 1. ARPA 2. ARPANET 3. Transmission control Protocol (TCP) 4. Internetworking Protocol (IP)  Internet today  Internet service providers (ISPs)

16. 1-4 PROTOCOLS AND STANDARDS  Protocols (rules) 1. Why do we need protocols? 2. Key elements of protocols a) Syntax b) Semantics c) Timing  Standards 1. De facto vs. De jure 2. Organizations 3. Internet standards (Internet draft & RFC)

17. Chapter 2 Network Models

18. Figure 2.2 Seven layers of the OSI model

19. Figure 2.3 The interaction between layers in the OSI model Network support layers User support layers

20. Figure 2.4 An exchange using the OSI model

21. LAYERS IN THE OSI MODEL Figure 2.5 Physical layer The physical layer is responsible for movements of individual bits from one hop (node) to the next.

22. Figure 2.6 Data link layer The data link layer is responsible for moving frames from one hop (node) to the next.

23. Figure 2.8 Network layer The network layer is responsible for the delivery of individual packets from the source host to the destination host.

24. Figure 2.10 Transport layer The transport layer is responsible for the delivery of a message from one process to another.

25. Figure 2.12 Session layer The session layer is responsible for dialog control and synchronization.

26. Figure 2.13 Presentation layer The presentation layer is responsible for translation, compression, and encryption.

27. Figure 2.14 Application layer The application layer is responsible for providing services to the user.

28. Figure 2.15 Summary of layers

29. TCP/IP PROTOCOL SUITE 1.The layers in the TCP/IP protocol suite do not exactly match those in the OSI model. The original TCP/IP protocol suite was defined as having four layers: host-to-network, internet, transport, and application. 2.However, when TCP/IP is compared to OSI, we can say that the TCP/IP protocol suite is made of five layers: physical, data link, network, transport, and application. 3.Topics covered: 1.Physical and Data Link Layers 2.Network Layer 3.Transport Layer 4.Application Layer

30. Figure 2.16 TCP/IP and OSI model

31. Figure 2.18 Relationship of layers and addresses in TCP/IP

32. Chapter 3 Data and Signals

33. ANALOG AND DIGITAL To be transmitted, data must be transformed to electromagnetic signals. Data can be analog or digital. Analog data refers to information that is continuous; digital data refers to information that has discrete states. Analog data take on continuous values. Digital data take on discrete values. Signals can be analog or digital. Analog signals can have an infinite number of values in a range; digital signals can have only a limited number of values. Analog and Digital Data Analog and Digital Signals Periodic and Nonperiodic Signals Topics discussed in this section:

34. Figure 3.1 Comparison of analog and digital signals

35. In data communications, we commonly use periodic analog signals and nonperiodic digital signals. Periodic signals: repeat patterns Nonperiodic signals: no patterns

36. PERIODIC ANALOG SIGNALS Periodic analog signals can be classified as simple or composite.Periodic analog signals can be classified as simple or composite. A simple periodic analog signal, a sine wave, cannot be decomposed into simpler signals.A simple periodic analog signal, a sine wave, cannot be decomposed into simpler signals. A composite periodic analog signal is composed of multiple sine waves.A composite periodic analog signal is composed of multiple sine waves. Sine Wave Wavelength Time and Frequency Domain Composite Signals Bandwidth Topics discussed in this section:

37. Figure 3.2 A sine wave Peak amplitude Frequency Phase

38. Frequency and period are the inverse of each other.

39. Table 3.1 Units of period and frequency

40. Frequency is the rate of change with respect to time. Change in a short span of time means high frequency. Change over a long span of time means low frequency. If a signal does not change at all, its frequency is zero. If a signal changes instantaneously, its frequency is infinite.

41. Figure 3.5 Three sine waves with the same amplitude and frequency, but different phases

42. Figure 3.6 Wavelength and period Wavelength is the distance a simple signal can travel in one period. Wavelength (w) = signal velocity x period Recall: period = 1 / frequency

43. Figure 3.7 The time-domain and frequency-domain plots of a sine wave A complete sine wave in the time domain can be represented by one single spike in the frequency domain.

44. Figure 3.8 The time domain and frequency domain of three sine waves The frequency domain is more compact and useful when we are dealing with more than one sine wave.

45. A single-frequency sine wave is not useful in data communications; we need to send a composite signal. A composite signal is made of many simple sine waves. According to Fourier analysis, any composite signal is a combination of simple sine waves with different frequencies, amplitudes, and phases. If the composite signal is periodic, the decomposition gives a series of signals with discrete frequencies; if the composite signal is nonperiodic, the decomposition gives a combination of sine waves with continuous frequencies. Sine Waves and Composite Signals

46. Figure 3.12 The bandwidth of periodic and nonperiodic composite signals

47. DIGITAL SIGNALS In addition to being represented by an analog signal, information can also be represented by a digital signal. For example, a 1 can be encoded as a positive voltage and a 0 as zero voltage. A digital signal can have more than two levels. In this case, we can send more than 1 bit for each level.

48. Bit rate: the number of bits sent in 1s, expressed in bits per second (bps). Frequency Vs. Bit Rate Frequency: the number of periods in 1s.

49. Figure 3.16 Two digital signals: one with two signal levels and the other with four signal levels

50. Wavelength is the distance an analog signal can travel in one period. Bit length is the distance one bit occupies on the transmission medium. Wavelength Vs. Bit length

51. Figure 3.17 The time and frequency domains of periodic and nonperiodic digital signals A digital signal is a composite analog signal with an infinite bandwidth.

52. Figure 3.18 Baseband transmission Baseband transmission: sending a digital signal over a channel without changing the digital signal to an analog signal.

53. Figure 3.19 Bandwidths of two low-pass channels

54. Figure 3.20 Baseband transmission using a dedicated medium Baseband transmission of a digital signal that preserves the shape of the digital signal is possible only if we have a low-pass channel with an infinite or very wide bandwidth.

55. Figure 3.21 Rough approximation of a digital signal using the first harmonic for worst case

56. Figure 3.22 Simulating a digital signal with first three harmonics

57. Table 3.2 Bandwidth requirements

58. Figure 3.23 Bandwidth of a bandpass channel Broadband transmission: changing the digital signal to an analog signal for transmission. Bandpass channel: a channel with a bandwidth that does not start from zero.

59. TRANSMISSION IMPAIRMENT Signals travel through transmission media, which are not perfect. The imperfection causes signal impairment. This means that the signal at the beginning of the medium is not the same as the signal at the end of the medium. What is sent is not what is received. Three causes of impairment are attenuation, distortion, and noise.

60. Figure 3.26 Attenuation Decibel: measures the relative strengths of two signals or one signal at two different points. It’s negative if a signal is attenuated and positive if a signal is amplified.

61. Sometimes the decibel is used to measure signal power in milliwatts. In this case, it is referred to as dB m and is calculated as dB m = 10 log10 P m, where P m is the power in milliwatts. Example 3.29

62. Figure 3.28 Distortion

63. Figure 3.29 Noise SNR = average signal power/average noise power Thermal Induced Crosstalk Impulse

64. The values of SNR and SNR dB for a noiseless channel are Example 3.32 We can never achieve this ratio in real life; it is an ideal.

65. Figure 3.30 Two cases of SNR: a high SNR and a low SNR

66. DATA RATE LIMITS A very important consideration in data communications is how fast we can send data, in bits per second, over a channel. Data rate depends on three factors: 1. The bandwidth available 1. The bandwidth available 2. The level of the signals we use 2. The level of the signals we use 3. The quality of the channel (the level of noise) 3. The quality of the channel (the level of noise) Noiseless Channel: Nyquist Bit Rate Noisy Channel: Shannon Capacity Using Both Limits Topics discussed in this section:

67. Increasing the levels of a signal may reduce the reliability of the system. Nyquist bit rate = 2 x bandwidth x log 2 L

68. In reality we can not have a noiseless channel. Shannon capacity = bandwidth x log 2 (1+SNR)

69. For practical purposes, when the SNR is very high, we can assume that SNR + 1 is almost the same as SNR. In these cases, the theoretical channel capacity can be simplified to Example 3.40 For example, we can calculate the theoretical capacity of the previous example as

70. The Shannon capacity gives us the upper limit; the Nyquist formula tells us how many signal levels we need.

71. PERFORMANCE Bandwidth Throughput Latency (Delay) Bandwidth-Delay Product

72. In networking, we use the term bandwidth in two contexts. ❏ The first, bandwidth in hertz, refers to the range of frequencies in a composite signal or the range of frequencies that a channel can pass. ❏ The second, bandwidth in bits per second, refers to the speed of bit transmission in a channel or link.

73. Latency (Delay): Propagation time Transmission time Queuing time Processing delay