CS 414 - Spring 2012 CS 414 – Multimedia Systems Design Lecture 32 – Media Server (Part 2) Klara...

CS 414 - Spring 2012

CS 414 – Multimedia Systems Design Lecture 32 – Media Server (Part 2)

Klara Nahrstedt

Spring 2012

Administrative

MP3 posted, April 10, 2012 MP3 deadline April 28, 5pm (Saturday) MP3 presentations

Monday, April 30, 5-7pm


Covered Aspects of Multimedia

Image/VideoCapture

MediaServerStorage

Transmission

CompressionProcessing

Audio/VideoPresentationPlaybackAudio/Video

Perception/ Playback

Audio InformationRepresentation

Transmission

AudioCapture

A/V Playback

Image/Video InformationRepresentation


Video Server Flickr Flickr – image and video hosting website In November 2007

Flickr hosted 2 Billion Photos In August 2009,

Flickr hosted 62 databases across 124 servers In September 2010,

Fickr hosted more than 5 billion images Developed by Ludicorp, Vancouver, 2004, now owned by Yahoo!

June 2011 51 Million registered members

In August 2011 Flickr hosted 6 billion photos

Outline Media Server Disk Scheduling and

Admission Control Media Server File System Issues


Media Server Architecture


Storage device

Disk controller

Storage management

File System

Memory Management

Content Directory

Network Attachment

Incoming requestDelivered data

Review - EDF Example


Note: Consider that block number Implicitly encapsulates the disk track number

8

Review - Elevator (SCAN) Method

Take the closest request in the direction of travel

Real implementations do not go to the end (called LOOK)

Pros Bounded time for each request

Cons Request at the other end will

take a while

0 199

Arriving Requests in Request Queue98, 183, 37, 122, 14, 124, 65, 67Served Request at Disk Controller(37, 14, 0, 65, 67, 98, 122, 124, 183)

53

SCAN-EDF Scheduling Algorithm Combination of SCAN and EDF algorithms Each disk block request tagged with

augmented deadline Add to each deadline perturbation

Policy: SCAN-EDF chooses the earliest deadline If requests with same deadline, then choose

request according to scan direction


Implementation of SCAN-EDF Notation:

Di be deadline of disk block request ‘i’

Ni be track (block) position on disk

Nmax be maximum number of disk tracks

Deadline Modification: Di + f(Ni)

f(Ni) converts track number of ‘i’ into a small perturbation of deadline

Perturbation small enough so that Di + f(Ni) ≤ Dj + f(Nj) for Di ≤ Dj

Possible f(Ni) = Ni/Nmax


SCAN EDF Example (Nmax = 100)


Admission Control


Client 1 retrieves K1 blocks in oneround

Client 2 retrievesK2 blocks

Client 3 retrievesK3 blocks

Client 4 retrieves K4 blocks

Server

Admission Control Disk block requests are timed

Media server must determine admit a stream serve (schedule) a stream without having negative effect on

other streams already serviced.

Deterministic Guarantees Admission control considers worst case scenario when admitting

new stream Constrained Disk Placement Example: M - size of blocks, G –

size of gabs, rdt – data transfer of disk


)/(sec

)(sec)(sec

storsr

torsGtorsMT

dtplay

Media Server Architecture


Storage device

Disk controller

Storage management

File System

Memory Management

Content Directory

Network Attachment

Incoming requestDelivered data

Multimedia File System

File Placement File allocation tables/Index tables Additional File System Operations

Fast forwardRewind

Block sizes


Multimedia File Systems Real-time Characteristics

Read operation must be executed before well-defined deadline with small jitter

Additional buffers smooth data

File Size Can be very large even those compressed Files larger than 232 bytes

Multiple Correlated Data Streams Retrieval of a movie requires processing and synch of

audio and video streams


Placement of Multiple MM Files on Single Disk Popularity concept among multimedia content -

very important Take popularity into account when placing

movies on disk Model of popularity distribution – Zipf’s Law

Movies are kth ranked if their probability of customer usage is C/k,

C = normalization factor

Condition holds: C/1 + C/2 + … C/N = 1, N is number of customers


Example Assume N = 5 movies Problem: what is the probability that the next

customer picks 3rd ranked movie? Solution:

Solve C from the equation C/1 + C/2 + C/3 + C/4 + C/5 = 1

C = 0.437Probability to pick 3rd ranked movie is C/3 =

0.437/3 = 0.1456


Placement Algorithm for Multiple Files on Single Disk Organ-Pipe Algorithms (Grossman and

Silverman 1973)


Middle of disk (in case of traditional disk layout)

1st rank (most popular movie)

2nd ranked movie3rd 4th

5th 6th

7th 8th

9th

Note: In case of ZBR disk layout , place most popular disks at the outer tracks

Placement of Mapping Tables Fundamental Issue: keep track of which disk

blocks belong to each file (I-nodes in UNIX) For continuous files/contiguous placement

don’t need maps For scattered files

Need maps Linked lists (inefficient for multimedia files) File allocation tables (FAT)


Indexing and FAT


I Frame

Higher Level Index TablePer File

P Frame

B Frame

P Frame

Block I1 Location PTR



Block P11 Location PTR


Block B1 Location PTR



File Allocation Table

………..

…………..

Constant and Real-time Retrieval of MM Data Retrieve index in real-time Retrieve block information from FAT Retrieve data from disk in real-time Real-time playback

Implement linked list

Random seek (Fast Forward, Rewind) Implement indexing

MM File Maps include metadata about MM objects: creator of video, sync info


Fast Forward and Rewind(Implementation) Play back media at higher rate

Not practical solution

Continue playback at normal rate, but skip frames Define skip steps, e.g. skip every 3rd, or 5th frame Be careful about interdependencies within MPEG frames

Approaches for FF: Create a separate and highly compressed file Categorize each frame as relevant or irrelevant Intelligent arrangement of blocks for FF


Block Size Issues in File Organization Small Block Sizes

Use smaller block sizes, smaller than average frame size

Organization Strategy: Constant Time Length Need Metadata structure, called Frame Index

Frame means a time frame within a movie Under the time frame read all blocks (audio, video,

text) belonging to this time frame


A V

V T

Frameindex

MovieTimeline

A V

V T

………

V A

V

Block Size Issues Large Block Size

Use large blocks (e.g., 256 KB) which include multiple audio/video/text frames

Organization Strategy: Constant Data Length Need Metadata structure, called Block Index

Each block contains multiple movie frames


A V

V

V

A AA

V

VV

BlockIndex

Tradeoffs

Frame index : needs large RAM usage while movie is playing, however little disk wastage

Block index (if frames are not split across blocks): need low RAM usage, but major disk wastage – internal disk fragmentation

Block index(if frames are split across blocks): need low Ram usage, no disk wastage, extra seek times


Conclusion

Designers of VOD systems strive to achieve low access latency for customers

Challenges: Handle large amount of customers (clients)Maintain low cost of operation Provide acceptable access latency


CS 414 - Spring 2012 CS 414 – Multimedia Systems Design Lecture 32 – Media Server (Part 2) Klara...

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