CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 26 – Media Server (Part 2) Klara...

CS 414 - Spring 2011

CS 414 – Multimedia Systems Design Lecture 26 – Media Server (Part 2)

Klara Nahrstedt

Spring 2011

Outline Storage Management

Multimedia Data Placement Strategies on Disk

Multiple Disks and Multimedia RAID

Data Striping Group Creation

Disk Management Data Interleaving Disk Scheduling

EDF ; SCAN-EDF


Client/Server Video-on-Demand System


Video-on-Demand Systems must be designed with goals: Avoid starvation Minimize buffer space requirement Minimize initiation latency (video startup

time) Optimize cost


Some Facts on YouTube Video Service (from 2009) Checked with

http://www.wired.com/epicenter/2009/10/youtube-over-one-billion-videos-served-per-day

/

Over 1 billion videos per day Bandwidth accounts for about 51% of expenses

-- with a run rate of $1 million per day -- with content licensing accounting for 36%

http://www.multichannel.com/article/191223-YouTube_May_Lose_470_Million_In_2009_Analysts.php


YouTube Video Server (2010)

http://tech.fortune.cnn.com/2010/05/17/youtube-at-5-years-old-2-billion-served-per-day/

May 2010, 2 Billion videos served per day More than 24 hours of video uploaded

every minute Videos usually less than 10 minutes long


Media Server Architecture


Storage device

Disk controller (Disk Management)

Storage management

File System

Memory Management

Content Directory

Network Attachment

Incoming requestDelivered data

Storage Management Storage access time to read/write disk

block is determined by 3 componentsSeek Time

Time required for the movement of read/write head

Rotational Time (Latency Time) Time during which transfer cannot proceed until the right

block or sector rotates under read/write head

Data Transfer Time Time needed for data to copy from disk into main memory


Placement of MM Data Blocks on Single Disk


Continuous Placement Scattered Placement

Simple to implement, but subject to fragmentation

Avoids fragmentation

Enormous copying overhead during insert/delete to maintain continuity

Avoid copying overhead

When reading file, only one seek required to position the disk head at the start of data

When reading file, seek operation incurs for each block , hence intrafile seek

Intra-file Seek Time Intra-file seek – can be avoided in scattered layout

if the amount read from a stream always evenly divides block

Solution: select sufficient large block and read one block in each round If more than one block is required to prevent starvation

prior to next read, deal with intra-file seek Solution: constrained placement or log-structure

placement


Scattered Non-continuous Placement


Constrained Placement Approach: separation between successive file blocks

is bounded Bound on separation – not enforced for each pair of

successive blocks, but only on average over finite sequence of blocks

Attractive for small block sizes Implementation – expensive

For constrained latency to yield full benefit, scheduling algorithm must retrieve immediately all blocks for a given stream before switching to another stream


Log-Structure Placement This approach writes modified blocks sequentially

in a large contiguous space, instead of requiring seek for each block in stream when writing (recording) Reduction of disk seeks Large performance improvements during recording,

editing video and audio

Problem: bad performance during playback Implementation: complex


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

Need for Multiple Disks Solutions for Media Server

Limitation of Single Disk: Disk Throughput

Approach: 1 Maintain multiple copies of the same file on different disks Very expensive

Approach 2: Scatter multimedia file across multiple disks


Approach: Data Striping RAID (Redundant Arrays of

Inexpensive Disks) Addresses both performance

and security (0-6) RAID levels – different

approach at combining performance enhancements with security/fault-tolerance enhancements

Disks spindle synchronously Operate in lock-step parallel

mode Striping improves BW, but does not

improve seek or rotational delayCS 414 - Spring 2011

Data Striping – Group Creation


Multiple RAID: Creation of Subgroups of disks into independent logical disk arrays; limits # of disks per file

Declustering: Groups are not made up of complete disks ; # of disks for any stripe is fixed and of same size, but disks on which stripe is located differs

Dynamic Declustering: Non - static strip allocation to disks

Storage/Disk Management Disk access – slow and costly Reduce disk access

Use block caches (anticipate future reads or writes)

Reduce disk arm motion Blocks accesses in sequence (continuously) ,

place together on one cylinder Interleaved vs non-interleaved storage


Data Interleaving


Data InterleavingOn Multiple Disks(Disks are not Synchronized)

Data InterleavingOn single disk(consecutive blocks are placed on The same cylinderBut in interleaved way

Disk Scheduling Policies Goal of Scheduling in Traditional Disk

Management Reduce cost of seek time Achieve high throughput Provide fair disk access

Goal of Scheduling in Multimedia Disk Management Meet deadline of all time-critical tasks Keep necessary buffer requirements low Serve many streams concurrently Find balance between time constraints and efficiency


Disk Scheduling Framework Must support multiple QoS levels and requests


Source: Reddy et al, “Disk Scheduling in a Multimedia I/O System”, ACM TOMCCAP 2005

EDF (Earliest Deadline First) Disk Scheduling

Each disk block request is tagged with deadlineVery good scheduling policy for periodic requests

Policy: Schedule disk block request with earliest deadlineExcessive seek time – high overheadPure EDF must be adapted or combined with file

system strategies


EDF Example


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

Conclusion

Disk Scheduling – important component in the timely delivery of streams

Admission should be done if one cares not to over subscribe


CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 26 – Media Server (Part 2) Klara...

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