Multimedia Systems

CS-502 Operating Systems

Outline

• Requirements and challenges for audio and video in computer systems

• Systems for multimedia• Compression and bandwidth• Processor scheduling• File, disk, and network management

What do we mean by “multimedia”

• Audio and video within a computer system– CD’s & DVD’s– Computer hard drive

• Live broadcast & web casts– Webcams, Skype, …

• Video on demand– Pause, fast forward, reverse, etc.

• Interactive meetings– Presentations with 2-way audio– Teleconferencing

• Interactive gaming• …

Requirements

• “Smooth” audio and video– Deterioration in quality >> jerky playback– Note: human is more sensitive to jitter in audio

than to jitter in video!

• Audio/video on PC’s doing something else• Multiple concurrent streams

– Video & multimedia servers– TiVo, etc.

• Wide range of network bandwidths

System and OS Challenges

• Bandwidths and Compression

• Jitter

• Processor Scheduling

• Disk Scheduling

• Network Streaming

Some System Architectures

• Simple: – Data paths for audio/video that are separate

from computational data paths

• Modern– Fast system bus, CPU, devices

• Video server– Disk farm and multiple streams

audio stream

CD-ROM drive

System Organization (simple)

• Separate data path for audio stream• Main system bus and CPU were too busy/slow to

handle real-time audio

CPU

Memory

memory bus

Device Sound card

video stream viaISA & bridge to

graphics card

audio stream viaISA bridge to

sound card

System Organization (typical Pentium)

ISA bridge

IDE disk

Main Memory

CPULevel

2 cache

Bridge Moni-tor

Graphics card

USB

Key-board

Mouse

Ether-net

SCSI

ModemSoundcard

Printer

PCI bus

ISA bus

AGP Port

Video Server

• Multiple CPUs

• Disk farm– 1000s of disks

• Multiple high-bandwidth network links– Cable TV– Video on demand– Internet

Why Compression? – CD-quality audio

• 22,050 Hz 44,100 samples/sec• 16 bits per sample

• Two channels 176,000 bytes/sec 1.4 mbits/sec

– Okay for a modern PC

– Not okay for 56 kb/sec modem (speed) or iPod (space)!

• MP-3 0.14 mbits/sec (10:1)– Same audio quality!

– Compression ratio varies with type of music

Why Compression? – Video

• “Standard” TV frame = 640 480 pixels @ 25-30 frames/sec (fps) 9,216,000 pixels/sec = 27,648,000 bytes/sec

• HDTV = 1280 720 pixels @ 30 fps 82,944,000 bytes/sec

• Typical movie 133 minutes approx. 220 gigabytes!

• DVD holds ~ 4.7 gigabytes average of ~ 620 kilobytes/sec!

• “Standard” movie of 133 minutes requires serious compression just to fit onto DVD

Video Compression Requirements

• Compression ratio > 50:1• i.e., 220 gigabytes:4.7 gigabytes

• Visually indistinguishable from original• Even when paused

• Fast, cheap decoder• Slow encoder is okay

• VCR controls• Pause, fast forward, reverse

Video Compression Standards

• MPEG (Motion Picture Experts Group)– Based on JPEG (Joint Photographic Experts Group)– Multi-layer

• Layer 1 = system and timing information• Layer 2 = video stream• Layer 3 = audio and text streams

• Three standards– MPEG-1 – 352240 frames; < 1.5 mb/sec ( < VHS quality)

• Layer 3 = MP3 Audio standard

– MPEG-2 – standard TV & HDTV; 1.5-15 mb/sec• DVD encoding

– MPEG-4 – combined audio, video, graphics• 2D & 3D animations

JPEG compression (single frame)

1. Convert RGB into YIQ• Y = luminance (i.e., brightness) ~ black-white TV• I, Q = chrominance (similar to saturation and hue)

Reason: Human eye is more sensitive to luminance than to color (rods vs. cones)

2. Down-sample I, Q channels• i.e., average over 22 pixels to reduce resolution• lossy compression, but barely noticeable to eye

3. Partition each channel into 88 blocks• 4800 Y blocks, 1200 each I & Q blocks

JPEG (continued)

JPEG (continued)

JPEG (continued)

4. Calculate Discrete Cosine Transform (DCT) of each 88 block

• What is a Discrete Cosine Transform?

5. Divide 88 block of DCT values by 88 quantization table

• Effectively throwing away higher frequencies

6. Linearize 88 block, run-length encode, and apply a Huffman code to reduce to a small fraction of original size (in bytes)

JPEG (concluded)

7. Store or transmit 88 quantization table followed by list of compressed blocks

• Achieves 20:1 compression with good visual characteristics

• Higher compression ratios possible with visible degradation

• JPEG algorithm executed backwards to recover image

• Visually indistinguishable from original @ 20:1

• JPEG algorithm is symmetric• Same speed forwards and backwards

MPEG

• JPEG-like encoding of each frame• Takes advantage of temporal locality• I.e., each frame usually shares similarities

with previous frame encode and transmit only differences

• Sometimes an object moves relative to background find object in previous frame, calculate

difference, apply motion vector

Temporal Locality (example)

Consecutive Video Frames

MPEG organization

• Three types of frames– I-frame: Intracoded or Independent.

• Full JPEG-encoded frame• Occurs at intervals of a second or so• Also at start of every scene

– P-frame: Predictive frame• Difference from previous frame

– B-frame: Bidirectional frame• Like p-frame but difference from both previous and next frame

I B BB P B BB P B BB P B BB I B BB P B BB P

MPEG Characteristics

• Non-uniform data rate!

• Compression ratios of 50:1 – 80:1 are readily obtainable

• Asymmetric algorithm– Fast decode (like JPEG)– Encode requires image search and analysis to

get high quality differences

• Decoding chips on graphics cards available

MPEG Problem – Fast Forward/Reverse

• Cannot simply skip frames– Next desired frame might be B or P derived

from a skipped frame

• Options:– Separate fast forward and fast reverse files

• MPEG encoding of every nth frame

• See Tanenbaum §7.5.1 – video-on-demand server

– Display only I and P frames• If B frame is needed, derive from nearest I or P

“Movie” File Organization

• One MPEG-2 video stream

• Multiple audio streams• Multiple languages

• Multiple text streams• Subtitles in multiple languages

• All interleaved

Challenge

• How to get the contents of a movie file from disk or DVD drive to video screen and speakers.– Fixed frame rate (25 or 30 fps)

– Steady audio rate

– Bounded jitter

• Classical problem in real-time scheduling– Obscure niche become mainstream!

– See Silbershatz, Chapter 19

Processor Scheduling for Real-TimeRate Monotonic Scheduling (RMS)

• Assume m periodic processes– Process i requires Ci msec of processing time every Pi

msec.

– Equal processing every interval — like clockwork!

• Assume

• Let priority of process i be

• Let priority of non-real-time processes be 0

11

m

i i

i

P

C

iP

1

Rate Monotonic Scheduling (continued)

• Then using these priorities in scheduler guarantees the needed Quality of Service (QoS), provided that

)12(1

1

mm

i i

i mP

C

• Asymtotically approaches ln 2 as m • I.e., must maintain some slack in scheduling• Assumes fixed amount of processing per periodic

task– Not MPEG!

Processor Scheduling for Real-TimeEarliest Deadline First (EDF) Scheduling

• When each process i become ready, it announces deadline Di for its next task.

• Scheduler always assigns processor to process with earliest deadline.

• May pre-empt other real-time processes

Earliest Deadline First Scheduling (continued)

• No assumption of periodicity• No assumption of uniform processing times

• Theorem: If any scheduling policy can satisfy QoS requirement for a sequence of real time tasks, then EDF can also satisfy it.– Proof: If i scheduled before i+1, but Di+1 < Di,

then i and i+1 can be interchanged without affecting QoS guarantee to either one.

Earliest Deadline First Scheduling (continued)

• EDF is more complex scheduling algorithm• Priorities are dynamically calculated

• Processes must know deadlines for tasks

• EDF can make higher use of processor than RMS

• Up to 100%

• However, it is usually a good idea to build in some slack

Multimedia File & Disk Management

• Single movie or multimedia file on PC disk– Interleave audio, video, etc.

• So temporally equivalent blocks are near each other

– Attempt contiguous allocation• Avoid seeks within a frame

TextFrame

AudioFrame

File organization – Frame vs. Block

• Frame organization• Small disk blocks (4-16 Kbytes)• Frame index entries point to starting block for each frame• Frames vary in size (MPEG)• Advantage: very little storage fragmentation• Disadvantage: large frame table in RAM

• Block organization• Large disk block (256 Kbytes)• Block index entries point to first I-frame of a sequence• Multiple frames per block• Advantage: much smaller block table in RAM• Disadvantage: large storage fragmentation on disk

Frame vs. Block organization

smaller larger

File Placement on Server

• Random

• Striped

• “Organ pipe” allocation– Most popular video in center of disk– Next most popular on either side of it– Etc.– Least popular at edges of disk– Minimizes seek distance

Disk Scheduling (server)

• Scheduling disk activity is just as important as scheduling processor activity

• Advantage:– Predictability• Unlike disk activity of ordinary computing

• In server, there will be multiple disk requests in each frame interval

• One request per frame for each concurrent video stream

Disk Scheduling (continued)

• SCAN (Elevator) algorithm for each frame interval

• Sort by cylinder #

• Complete in time for start of next frame interval

• Variation – SCAN–EDF:• Sort requests by deadline

• Group similar deadlines together, apply SCAN to group

• Particularly useful for non-uniform block sizes and frame intervals

Network Streaming

• Traditional HTTP• Stateless

• Server responds to each request independently

• Real-Time Streaming Protocol (RTSP)• Client initiates a “push” request for stream

• Server provides media stream at frame rate

Push vs. Pull server

Bandwidth Negotiation

• Client (or application) provides feedback to server to adjust bandwidth

• E.g., – Windows Media Player– RealPlayer– QuickTime

Conclusion

• Multimedia computing is challenging• Possible with modern computers

• Compression is essential, especially for video

• Real-time computing techniques move into mainstream

• Processor and disk scheduling

• There is much more to this subject than fits into one class

SOME USEFUL THEOREMS AND TRANSFORMATION

Digression on Transforms

• Fourier’s theorem:–– Every continuous periodic function can be

reduced to the sum of a series of sine waves– The Fourier transform is a representation of

that function in terms of the frequencies of those sine waves

– Original function can be recovered from its Fourier transform

• Fourier transforms occur frequently in nature!

Nyquist’s Theorem (1924)

• If a continuous function is sampled at a frequency 2f, then the function can be recovered from those samples provided that its maximum Fourier frequency is f.

Discrete Cosine Transform

• A form of the Fourier Transform

• When applied to an 88 block of samples (i.e. pixel values) yields an 88 block of spatial frequencies

• Original 88 block of samples can be recovered from its DCT.– Assuming infinite arithmetic precision

More on Nyquist• If arithmetic precision is not infinite, we get

quantization error during sampling• Recovered signal has quantization noise

• i.e., a lossy transform