Making Connections Efficient: Multiplexing and Compression Chapter Five Making Connections Efficient: Multiplexing and Compression

Objective สามารถอธิบายการมัลติเพล็กซ์แบบแบ่งความถี่ และระบุแอปพลิเคชั่นที่ใช้ รวมถึงข้อดี ข้อเสียที่เกิดขึ้นได้ สามารถอธิบายการมัลติเพล็กซ์แบบแบ่งเวลาในรูปแบบซิงโครไนซ์ และระบุแอปพลิเคชั่นที่ใช้ รวมถึงข้อดี ข้อเสียที่เกิดขึ้นได้ สามารถระบุคุณสมบัติพื้นฐานการมัลติเพล็กของ T-1, ISDN และระบบโทรศัพท์ SONET/SDH

Objective สามารถอธิบายการมัลติเพล็กซ์แบบแบ่งเวลาในรูปแบบสถิติ และระบุแอปพลิเคชั่นที่ใช้ รวมถึงข้อดี ข้อเสียที่เกิดขึ้นได้ สามารถบอกคุณสมบัติของการมัลติเพล็กซ์แบบแบ่งตามความยาวคลื่น รวมถึงข้อดี ข้อเสียที่เกิดขึ้นได้ สามารถอธิบายคุณลักษณะพื้นฐานของเทคโนโลยี Discrete Multitone (DMT) สามารถบอกคุณสมบัติหลักของการมัลติเพล็กซ์แบบแบ่งตามรหัส และข้อดี ข้อเสียที่เกิดขึ้นได้

Objective สามารถบอกความแตกต่างระหว่างการบีบอัดข้อมูลแบบสูญเสียข้อมูล และไม่มีการสูญเสียข้อมูลได้ สามารถระบุการทำงานพื้นฐานของการบีบอัดข้อมูลแบบ run-length, JPEG และ MP3 สามารถประยุกต์ใช้เทคนิคมัลติเพล็กซิ่ง กับสถานการณ์ทางธุรกิจทั่วๆไปได้

Chapter Five - Making Connections Efficient: Multiplexing and Compression Introduction Under the simplest conditions, a medium can carry only one signal at any moment in time For multiple signals to share a medium, the medium must somehow be divided, giving each signal a portion of the total bandwidth The current techniques include frequency division multiplexing, time division multiplexing, and code division multiplexing

Frequency Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Frequency Division Multiplexing Assignment of non-overlapping frequency ranges to each “user” or signal on a medium. Thus, all signals are transmitted at the same time, each using different frequencies A multiplexor accepts inputs and assigns frequencies to each device

Frequency Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Frequency Division Multiplexing The multiplexor is attached to a high-speed communications line A corresponding multiplexor, or demultiplexor, is on the end of the high-speed line and separates the multiplexed signals

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Frequency Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Frequency Division Multiplexing Analog signaling is used to transmit the data Broadcast radio and television, cable television, and cellular telephone systems use frequency division multiplexing This technique is the oldest multiplexing technique Since it involves analog signaling, it is more susceptible to noise

Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Time Division Multiplexing Sharing of the signal is accomplished by dividing available transmission time on a medium among users Digital signaling is used exclusively Time division multiplexing comes in two basic forms: Synchronous time division multiplexing Statistical time division multiplexing

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing The original time division multiplexing The multiplexor accepts input from attached devices in a round-robin fashion and transmits the data in a never ending pattern T-1 and ISDN telephone lines are common examples of synchronous time division multiplexing

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing If one device generates data at a faster rate than other devices, then the multiplexor must either sample the incoming data stream from that device more often than it samples the other devices, or buffer the faster incoming stream If a device has nothing to transmit, the multiplexor must still insert something into the multiplexed stream

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing So that the receiver may stay synchronized with the incoming data stream, the transmitting multiplexor can insert alternating 1s and 0s into the data stream

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing The T-1 multiplexor stream is a continuous series of frames

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing The ISDN multiplexor stream is a also a continuous series of frames. Each frame contains various control and sync info

Synchronous Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Synchronous Time Division Multiplexing Likewise, SONET incorporates a continuous series of frames.

Statistical Time Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Statistical Time Division Multiplexing A statistical multiplexor transmits the data from active workstations only If a workstation is not active, no space is wasted in the multiplexed stream A statistical multiplexor accepts the incoming data streams and creates a frame containing the data to be transmitted

Chapter Five - Making Connections Efficient: Multiplexing and Compression

To identify each piece of data, an address is included Chapter Five - Making Connections Efficient: Multiplexing and Compression To identify each piece of data, an address is included

If the data is of variable size, a length is also included Chapter Five - Making Connections Efficient: Multiplexing and Compression If the data is of variable size, a length is also included

Chapter Five - Making Connections Efficient: Multiplexing and Compression More precisely, the transmitted frame contains a collection of data groups

Wavelength Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Wavelength Division Multiplexing Wavelength division multiplexing multiplexes multiple data streams onto a single fiber optic line Different wavelength lasers (called lambdas) transmit the multiple signals

Wavelength Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Wavelength Division Multiplexing Each signal carried on the fiber can be transmitted at a different rate from the other signals Dense wavelength division multiplexing combines many (30, 40, 50 or more) onto one fiber Coarse wavelength division multiplexing combines only a few lambdas

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Discrete Multitone (DMT) Chapter Five - Making Connections Efficient: Multiplexing and Compression Discrete Multitone (DMT) A multiplexing technique commonly found in digital subscriber line (DSL) systems DMT combines hundreds of different signals, or subchannels, into one stream

Discrete Multitone (DMT) Chapter Five - Making Connections Efficient: Multiplexing and Compression Discrete Multitone (DMT) Each subchannel is quadrature amplitude modulated (recall eight phase angles, four with double amplitudes) Theoretically, 256 subchannels, each transmitting 60 kbps, yields 15.36 Mbps Unfortunately, there is noise

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing Also known as code division multiple access An advanced technique that allows multiple devices to transmit on the same frequencies at the same time Each mobile device is assigned a unique 64-bit code

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing To send a binary 1, a mobile device transmits the unique code To send a binary 0, a mobile devices transmits the inverse of the code

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing Receiver gets summed signal, multiplies it by receiver code, adds up the resulting values Interprets as a binary 1 if sum is near +64 Interprets as a binary 0 if sum is near -64

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing For simplicity, assume 8-bit code Three different mobile devices use the following codes: Mobile A: 10111001 Mobile B: 01101110 Mobile C: 11001101 Assume Mobile A sends a 1, B sends a 0, and C sends a 1

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing Signal code: 1-chip = +N volt; 0-chip = -N volt Three signals transmitted: Mobile A sends a 1, or 10111001, or +-+++--+ Mobile B sends a 0, or 10010001, or +--+---+ Mobile C sends a 1, or 11001101, or ++--++-+ Summed signal received by base station: +3, -1, -1, +1, +1, -1, -3, +3

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing Base station decode for Mobile A: Signal received: +3, -1, -1, +1, +1, -1, -3, +3 Mobile A’s code: +1, -1, +1, +1, +1, -1, -1, +1 Product result: +3, +1, -1, +1, +1, +1, +3, +3 Sum of Products: +12 Decode rule: For result near +8, data is binary 1

Code Division Multiplexing Chapter Five - Making Connections Efficient: Multiplexing and Compression Code Division Multiplexing Base station decode for Mobile B: Signal received: +3, -1, -1, +1, +1, -1, -3, +3 Mobile A’s code: -1, +1, +1, -1, +1, +1, +1, -1 Product result: -3, -1, -1, -1, +1, -1, -3, -3 Sum of Products: -12 Decode rule: For result near -8, data is binary 0

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Compression This is another technique used to squeeze more data over a communications line If you can compress a data file down to ½ of its original size, the file will obviously transfer in less time Two basic groups of compression: Lossless – when data is uncompressed, original data returns Lossy – when data is uncompressed, you do not have the original data

Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Compression Compress a financial file? You want lossless. Compress a video image, movie, or audio file? Lossy is OK Examples of lossless compression include Huffman codes, run-length compression, and Lempel-Ziv compression Examples of lossy compression include MPEG, JPEG, MP3

Run-Length Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Run-Length Compression Replace runs of 0s with a count of how many 0s. 00000000000000100000000011000000000000000000001000…001100000000000 ^ (30 0s) 14 9 0 20 30 0 11

Run-Length Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Run-Length Compression Now replace each decimal value with a 4-bit binary value (nibble). Note: If you need to code a value larger than 15, you need to use two code two consecutive 4-bit nibbles. The first is decimal 15, or binary 1111, and the second nibble is the remainder. For example, if the decimal value is 20, you would code 1111 0101 which is equivalent to 15 + 5. If you want to code the value 15, you still need two nibbles: 1111 0000. The rule is that if you ever have a nibble of 1111, you must follow it with another nibble.

Relative or Differential Encoding (Lossy) Chapter Five - Making Connections Efficient: Multiplexing and Compression Relative or Differential Encoding (Lossy) Video does not compress well using run-length encoding In one color video frame, not much is alike But what about from frame to frame? Send a frame, store it in a buffer Next frame is just difference from previous frame Then store that frame in buffer, etc.

Chapter Five - Making Connections Efficient: Multiplexing and Compression 5 7 6 2 8 6 6 3 5 6 6 5 7 5 5 6 3 2 4 7 8 4 6 8 5 6 4 8 8 5 5 1 2 9 8 6 5 5 6 6 First Frame 5 7 6 2 8 6 6 3 5 6 6 5 7 6 5 6 3 2 3 7 8 4 6 8 5 6 4 8 8 5 5 1 3 9 8 6 5 5 7 6 Second Frame 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 -1 0 0 0 1 0 0 0 0 0 1 0 Difference

Image Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Image Compression One image - JPEG, or continuous images such as video - MPEG A color picture can be defined by red/green/blue, or luminance / chrominance / chrominance which are based on RGB values Either way, you have 3 values, each 8 bits, or 24 bits total (224 colors!)

Image Compression Chapter Five - Making Connections Efficient: Multiplexing and Compression Image Compression A VGA screen is 640 x 480 pixels 24 bits x 640 x 480 = 7,372,800 bits. Ouch! And video comes at you 30 images per second. Double Ouch! We need compression!

JPEG Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Joint Photographic Experts Group Compresses still images Lossy JPEG compression consists of 3 phases: Discrete cosine transformations (DCT) Quantization Encoding

JPEG Step 1 -DCT Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Step 1 -DCT Divide image into a series of 8x8 pixel blocks If the original image was 640x480 pixels, the new picture would be 80 blocks x 60 blocks (next slide) If B&W, each pixel in 8x8 block is an 8-bit value (0-255) If color, each pixel is a 24-bit value (8 bits for red, 8 bits for blue, and 8 bits for green)

80 blocks 60 blocks 640 x 480 VGA Screen Image Divided into 8 x 8 Pixel Blocks

JPEG Step 1 -DCT Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Step 1 -DCT So what does DCT do? Takes an 8x8 array (P) and produces a new 8x8 array (T) using cosines T matrix contains a collection of values called spatial frequencies. These spatial frequencies relate directly to how much the pixel values change as a function of their positions in the block

JPEG Step 1 -DCT Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Step 1 -DCT An image with uniform color changes (little fine detail) has a P array with closely similar values and a corresponding T array with many zero values (next slide) An image with large color changes over a small area (lots of fine detail) has a P array with widely changing values, and thus a T array with many non-zero values

JPEG Step 2 -Quantization Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Step 2 -Quantization The human eye can’t see small differences in color So take T matrix and divide all values by 10. This will give us more zero entries. More 0s means more compression! But this is too lossy. And dividing all values by 10 doesn’t take into account that upper left of matrix has more action (the less subtle features of the image, or low spatial frequencies)

1 3 5 7 9 11 13 15 3 5 7 9 11 13 15 17 5 7 9 11 13 15 17 19 7 9 11 13 15 17 19 21 9 11 13 15 17 19 21 23 11 13 15 17 19 21 23 25 13 15 17 19 21 23 25 27 15 17 19 21 23 25 27 29 U matrix Q[i][j] = Round(T[i][j] / U[i][j]), for i = 0, 1, 2, …7 and j = 0, 1, 2, …7

JPEG Step 3 -Encoding Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG Step 3 -Encoding Now take the quantized matrix Q and perform run-length encoding on it But don’t just go across the rows. Longer runs of zeros if you perform the run-length encoding in a diagonal fashion

Chapter Five - Making Connections Efficient: Multiplexing and Compression

JPEG Chapter Five - Making Connections Efficient: Multiplexing and Compression JPEG How do you get the image back? Undo run-length encoding Multiply matrix Q by matrix U yielding matrix T Apply similar cosine calculations to get original P matrix back

Business Multiplexing In Action Chapter Five - Making Connections Efficient: Multiplexing and Compression Business Multiplexing In Action XYZ Corporation has two buildings separated by a distance of 300 meters. A 3-inch diameter tunnel extends underground between the two buildings. Building A has a mainframe computer and Building B has 66 terminals. List some efficient techniques to link the two buildings.

Chapter Five - Making Connections Efficient: Multiplexing and Compression

Possible Solutions Chapter Five - Making Connections Efficient: Multiplexing and Compression Possible Solutions Connect each terminal to the mainframe computer using separate point-to-point lines. Connect all the terminals to the mainframe computer using one multipoint line. Connect all the terminal outputs and use microwave transmissions to send the data to the mainframe. Collect all the terminal outputs using multiplexing and send the data to the mainframe computer using a conducted line.

แบ่งกลุ่มเพื่อวิเคราะห์ บริษัทแห่งหนึ่ง มีอาคาร 2 อาคารที่ห่างกัน 50 เมตร และมีอุโมงค์ขนาดใหญ่เชื่อมกันอยู่ระหว่าง 2 อาคาร อาคารแรกมีเครื่องคอมพิวเตอร์ 30 เครื่อง อาคารที่สองมีเครื่องเมนเฟรมอยู่ 1 เครื่อง จงบอกวิธีการเชื่อมต่อและวิธีการมัลติเพล็กซ์ ระหว่างคอมพิวเตอร์ และเครื่องเมนเฟรมที่ดีที่สุด พร้อมทั้งอธิบายเหตุผล และความเป็นไปได้ที่นักศึกษาได้เลือก

จงบอกความแตกต่างระหว่าง Synchronous TDM และ Statistical TDM Workshop จงบอกความแตกต่างระหว่าง Synchronous TDM และ Statistical TDM จงบอกประเภทของตัวกลางที่ใช้กับการมัลติเพล็กซ์แบบแบ่งตามความยาวคลื่น จงอธิบายว่า discrete multitone กับเทคนิคการมัลติเพล็กซ์แบบอื่นๆ ว่ามีความเหมือนและแตกต่างกันอย่างไร ให้นักศึกษาระบุข้อดีและข้อเสียอย่างละ 2 ข้อ สำหรับเทคนิคการมัลติเพล็กซ์ในแต่ละชนิด ดังต่อไปนี้ FDM, Synchronous TDM, Statistical TDM และ WDM

Workshop อุปกรณ์เคลื่อนที่ของนาย A มีการใช้การมัลติเพล็กซ์แบบแบ่งตามรหัส (CDM) และมีการกำหนดเลขฐานสอง คือ 10010111 อุปกรณ์เคลื่อนที่ของนาย B มีการใช้การมัลติเพล็กซ์แบบแบ่งตามรหัส (CDM) และมีการกำหนดเลขฐานสอง คือ 01001010 อุปกรณ์เคลื่อนที่ของนาย A มีการส่งแบบ a1 ขณะที่อุปกรณ์เคลื่อนที่ของนาย B มีการส่งแบบ a0 จงแสดงวิธีการคำนวณและผลลัพธ์จากการเข้ารหัสโดยละเอียด การบีบอัดข้อมูลแบบใด เหมาะสมกับประเภทของข้อมูลคล้ายๆกัน และมีจำนวนมากจึงมีประสิทธิภาพมากที่สุด