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Completing Lecture 1 and 2 Chapter 2 and 3 Handout #2

Recap of lectures discussing what happens at intermediate nodes in a network, file transfer process, digital vs analog signals, periodic signal characteristics, varying sine waves, electromagnetic signals, and digital signaling. The lectures cover the complexity of networking layers and the difference between data and signals in data transmission.

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Completing Lecture 1 and 2 Chapter 2 and 3 Handout #2

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  1. Completing Lecture 1 and 2Chapter 2 and 3Handout #2 Dr. Clincy Professor of CS Lecture

  2. Recap: What happens at the Intermediate Nodes ? Rx Tx 7 Intermediate Nodes 3 1 1 B C Q T A Z Lecture

  3. COMPLEXITY TO CONSIDER • Any particular node in an internetwork can be functioning as follows simultaneously: • Tx to other internetwork nodes • Rx from other internetwork nodes • Intermediate node to some other internetwork nodes Lecture

  4. The File Transfer Program issues a command to the Application Layer Application passes it to Presentation, which may reformat, encrypt, encode, compress, passes to Session (adds overhead) Session requests a connection, passes to Transport (adds overhead) Transport breaks file into chunks, adds error-checking and flow-control info, process-to-process, passes to Network (adds overhead) Network selects the data’s route (internetworking), passes to Data Link (adds overhead) Data Link adds error-control and flow-control info, passes to Physical (adds overhead) Physical translates bits to signal and transmits the signal, which includes information added by each layer OSI in Action: Outgoing File Transfer Lecture

  5. Physical receives signal and translates to bits, passes to Data Link Data Link checks for errors and performs flow control on bits, formulates bits into some formation (frames), passes to Network Network verifies routing (if intermediate node, determines next hop), passes to Transport Transport checks for errors and performs flow control on the chunks, reassembles the chunks, passes to Session Session determines if transfer is complete, may end session, passes to Presentation Presentation may reformat, perform conversions, decode, decrypt, decompress, pass to Application layer Application presents results to user (e.g. updates FTP program display) OSI in Action: Incoming File Transfer Lecture

  6. US Postal System Analogy • Illustrate how the US Postal System is very similar to how networking works • Will help students better understand (versus memorize) data comm and networking Upper Layers – creating and interpreting the signal, data or info Lower Layers – getting the signal from one place to the next

  7. Lectures 3 and 4Chapter 2 and 3Handout #2 Dr. Clincy Professor of CS Lecture

  8. Data Vs Signal • Fully explain the difference between signaland data before getting into the details (Digital Transmission) DATASIGNAL D D A (Analog Transmission) DATA SIGNAL A D A Lecture

  9. You probably have a good idea about digital and analog signals What about analog and digital data ?? Analog data examples Voice Images Digital data examples Text Digitized voice or images Data vs Signals Lecture

  10. Periodic Signal Characteristics If the signal’s pattern repeats over and over, we called these signals Periodic Signals Periodic Signals can be either Analog or Digital Lecture

  11. Analog Periodic Signal Case • Amplitude (A): signal value, measured in volts • Frequency (f): repetition rate, cycles per second or Hertz • Period (T): amount of time it takes for one repetition, T=1/f • Phase (f): relative position in time, measured in degrees • General sine wave is written as • S(t) = A sin(2pft + f) Lecture

  12. Varying S(t) = A sin(2pft + f) Lecture Note: 45 degrees because p is 180 degrees

  13. What is Wavelength ? • The distance an electromagnetic wave can travel in the amount of time it takes to oscillate through a complete cycle • Wavelength (w) = signal velocity x period or propagation speed x period • Recall: period = 1 / frequency Another perspective of Wavelength: how far did this signal travel AS the signal goes through a FULL cycle ? Lecture

  14. Electromagnetic Signals Electromagnetic signal can be expressed as a function of time or frequencyFunction of frequency (more important) Frequency-Domain Plot – peak amplitudes with respect to frequency Time-Domain Plot – amplitude changes with respect to time Different signals Lecture

  15. Electromagnetic Signals - Frequency • Electromagnetic signal can be expressed as a function of time or frequency • Function of frequency (more important) • Spectrum (range of frequencies) • Bandwidth (width of the spectrum) When we talk about spectrum, we mean the range of frequencies the electromagnetic signal takes on In the example, the signal has a Frequency range of f to 3f Therefore, a electromagnetic signal can be a collection (addition) of periodic analog Signals (Composite Signal) Lecture

  16. Composite Periodic Signal According to FOURIER ANALYSIS, a composite signal is a combination of sine waves with different amplitudes, frequencies and phases. Could converged to a square wave 3rd harmonic 9th harmonic Lecture

  17. Electromagnetic Spectrum for Transmission Media Tell them how to study this chart Lecture

  18. Digital Signaling • represented by square waves or pulses • Refers to transmission of electromagnetic pulses that represents 1’s and 0’s 1 cycle amplitude (volts) time (sec) frequency (hertz) = cycles per second Lecture

  19. Digital Signal Rate • Each bit’s signal has a certain duration • Example, given a data rate of 50 kbps (or 50,000 bps) • Each would have a 0.02 microseconds duration • Duration (or bit length) = 1/50000 = .00002 sec = .02 msec Lecture

  20. Digital Signal Sending 1 bit per level Sending 2 bits per level How many levels needed to send 5 bits at a time ???? # bits per level = log2 of (#oflevels) Lecture

  21. Baseband Transmission • In sending the digital signal over channel without changing the digital signal to an analog signal • Use low-pass channel – meaning the bandwidth can be as low as zero • Typical: 2 computers directly connected In baseband transmission, the required bandwidth is proportional to the bit rate; if we need to send bits faster, we need more bandwidth (the frequency will need to increase) Lecture

  22. Broadband Transmission • Broadband transmission or modulation means changing the digital signal to an analog signal for transmission • Modulation allows us to use a bandpass channel – a channel where the bandwidth doesn’t start at zero • Bandpass channels are more available than low-pass channels Lecture

  23. Channel Capacity • As we know, impairments limits the actual data rate realized • The actual rate realized at which data can be transmitted over a given path, under given conditions is called Channel Capacity • Four concepts • Data rate – the rate, in bps, the data can be communicated • Bandwidth – constrained by the Tx and transport medium – expressed in cycles per second or Hertz • Noise – average level of noise over the communication path • Error rate – the rate in which erroneous bits are received Lecture

  24. Impairments Lecture

  25. Attenuation Loss of energy – the signal can lose energy as it travels and try to overcome the resistance of the medium Decibel (dB) is a unit of measure that measures a signal’s lost or gain of strength – can be expressed in power or voltage dB = 10 log10 [P2/P1] = 20 log10 [V2/V1] Samples of the power or voltage taken at times 1 and 2. Lecture

  26. Distortion Distortion is when the signal changes its form. The each signal that makes up a composite signal could have different propagation speeds across the SAME medium – because of this, the different signals could have different delays (arriving at the receiver) – this causes a distortion. Lecture

  27. Noise Thermal Noise - the uncontrollable or random motion of electrons in the transport medium which creates an extra signal (not sent by the transmitter) Induced Noise – undesired devices acting as a transmitting antenna and those signals being picked up Cross Talk Noise – effect of one wire crossing another wire Impulse Noise – spikes in energy (ie lightning) Lecture

  28. Signal to Noise Ratio SNR = avg-signal-power/avg-noise-power High SNR – good (less corruption) Low SNR – bad (more noise than good power) SNR is described in Decibels (dB) SNRdB = 10 log10 SNR Lecture

  29. Shannon Equation • Shannon’s equation is used to determine the actual capacity of a channel given noise exist • C = B log2 (1 + SNR) • B = Bandwidth • C= Channel Capacity • SNR = Signal-to-noise ratio Actual ratio Lecture

  30. Chapter 3 and 4Handout #3 Dr. Clincy Professor of CS Lecture

  31. Nyquist Equation • Given no noise, determine the maximum bit rate • BitRate = 2 x B x log2 L • B is the bandwidth of the channel • L is the # signal levels used • BitRate unit is bps (bits per second) Having 2 levels is reliable because a Rx can interpret 2 levels – suppose you had 64 levels – less reliable or more complex to interpret Lecture

  32. Bandwidth Bandwidth is a measure of performance Bandwidth in hertz – range of frequencies Bandwidth in bps – bps a channel can handle (D/A case here (ie. Modem)) Lecture

  33. Throughput • Throughput is a measure of performance – how fast data can flow through a network • Bandwidth could be what the channel could handle however, Throughput would be the amount that actually flowed through • Bandwidth – potential • Throughput – actual Lecture

  34. Latency Latency is a performance measure – how long it takes an message to completely arrive to the receiver Latency consist of propagation time (time for a bit to travel from Tx to the Rx) Propagation time = distance/propagation-speed transmission time (time for a message to be sent) Transmission time = message-size/bandwidth queuing time (time each intermediate node holds the message) processing time (time each node spends processing the message) Note: if message is small, more bandwidth exists and therefore, the latency is more of propagation time versus transmission time Lecture

  35. The bandwidth-delay product defines the number of bits that can fill the link. • This is important when dealing with “full duplex” and being concerned about sending data to the Rx and receiving acknowledgments back from the Rx at the same time – before sending the next set of data Lecture

  36. Filling the link with bits for case 1 In other words, there can be no more than 5 bits at any time on the link. Lecture

  37. Filling the link with bits in case 2 5 bps 25 bps In other words, there can be no more than 25 bits at any time on the link. Lecture

  38. Chapter 4: Digital Transmission Physical Layer Issues Lecture

  39. Data Vs Signal • Fully explain the difference between signaland data before getting into the details Today’s Lecture (Digital Transmission) DATASIGNAL D D A Next Lecture (Analog Transmission) DATA SIGNAL A D A Lecture

  40. DIGITAL-TO-DIGITAL CONVERSION Can represent digital data by using digital signals. The conversion involves three techniques: line coding – converting bit sequences to signals block coding – adding redundancy for error detection scrambling– deals with the long zero-level pulse issue Line coding is always needed; Block coding and scrambling may or may not be needed. Lecture

  41. Line coding and decoding At Tx - Digital data represented as codes is converted to a digital signal via an encoder At Rx – Digital signal is converted back to digital codes via a decoder Lecture

  42. Signal element versus data element Data element - smallest entity representing info Signal element – shortest unit of a digital signal (carriers) r – is the ratio of # of data elements carried per signal element Example of adding extra signal elements for synchronization Example of increasing data rate Lecture

  43. Data Rate Versus Signal Rate Data rate (or bit rate) - # of data elements (or bits) transmitted in 1 second – bits-per-second is the unit Signal rate (pulse rate or baud rate) - # of signal elements transmitted in 1 second – baud is the unit OBJECTIVE ALWAYS: increase data rate while decreasing signal rate – more “bang” for the “buck” Is it intuitive that if you had a data pattern of all 0s or 1s, it would effect the signal rate ? Therefore to relate data-rate with signal-rate, the pattern matters. Worst Case Scenario – we need the maximum signaling rate (alternating 1/0s) Best Case Scenario – we need the minimum signaling rate (all 1/0s) Focus on average case S = c x N x 1/r N – data rate (bps) c – case factor S - # of signal elements r – ratio of data to signal Lecture

  44. Example A signal is carrying data in which one data element is encoded as one signal element ( r = 1). If the bit rate is 100 kbps, what is the average value of the baud rate if c is between 0 and 1? Solution We assume that the average value of c is 1/2 . The baud rate is then Lecture

  45. Bandwidth Now we understand what baud rate is And we understand what bit rate (or data rate) is Baud rate - # of carriers on the transport Data rate - # of passengers (or bits) in the carriers With this, we clearly see that baud rate effects bandwidth usage Signaling changes relate to frequency changes – therefore the bandwidth is proportionate with the baud rate: Bmin = c x N x 1/r or Nmax = 1/c x B x r minimum bandwidth maximum data rate (given the bandwidth) N – data rate C – case factor This formula is consistent with Nyquist formula r – data to signal ratio Lecture

  46. Example The maximum data rate of a channel (see Chapter 3) is Nmax = 2 × B × log2 L (defined by the Nyquist formula). Does this agree with the previous formula for Nmax? Solution A signal with L levels actually can carry log2L bits per level. If each level corresponds to one signal element and we assume the average case (c = 1/2), then we have Lecture

  47. Decoding Issue 1 Keep in mind the Rx decodes the digital signal – how is it done ? • Rx determines a “moving average” of the signal’s power or voltage levels • This average is called the baseline • Then the Rx compares incoming signal power to this average (or baseline) • If higher than the baseline, could be a 1 • If lower than the baseline, could be a 0 • In using such a technique, is it intuitive that long runs of 0s or 1s could skew the average (baseline) ?? – this is called baseline wandering (effects Rx’s ability to decode correctly) Lecture

  48. Decoding Issue 2 Effect of lack of synchronization For the Rx, to correctly read the signal, both the Tx and Rx “bit intervals” must be EXACT Example of Rx timing off – therefore decoding the wrong data from the signal To fix this, the Tx could insert timing info into the data that synchs the Rx to the start, middle and end of a pulse – these points could reset an out-of-synch Rx Lecture

  49. Example In a digital transmission, the receiver clock is 0.1 percent faster than the sender clock. How many extra bits per second does the receiver receive if the data rate is 1 kbps? How many if the data rate is 1 Mbps? Solution At 1 kbps, the receiver receives 1001 bps instead of 1000 bps. At 1 Mbps, the receiver receives 1,001,000 bps instead of 1,000,000 bps. NOTE: Keep in mind that a FASTER clock means SHORTER intervals Lecture

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