1. Distributed Multimedia Systems1

2. Examples of DMMS
And more!

3. Introduction
Definition: "A distributed multimedia system (DMS) is an integrated communication, computing, and information system that enables the processing, management, delivery, and presentation of synchronized multimedia information with quality-of-service guarantees."

4. Characteristics Delivering the streams of multimedia data
Audio samples, Video frames
To meet the timing requirements
QoS (Quality of Service)
Flexibility (adapting to user needs)
Availability
Scalability

5. Factors that affect a system
Server bandwidth
Cache space
Number of copies
The number of clients

6. Basic Schema Wide area gateway Video server Digital TV/radio
Video camera
and mike
Local network

7. Typical infrastructure components for multimedia applications

9. Different Designs and Architectures
Database
Proxy/information servers
Clients
Wired or wireless networks

10. Approaches Proxy-based approach Parallel or clustered servers approach
Varies based on clip duration, number of clients, bandwidth available, etc
Caching

11. Quality of Service (QoS)
DMMS are real-time systems as data must be delivered on time
Not critical – Some flexibility exists
Loss is acceptable when resync is possible.
“Acceptable” service is measured by:
Bandwidth (Throughput)
Latency (Access time)
Data Loss Rate (Acceptable loss ratio)

12. QoS Management “QoS Management” Resources include:
Process of managing resources to meet the Acceptable service criteria.
Resources include:
CPU / processing power
Network bandwidth
Buffer memory(on both ends)
Disk bandwidth
Other factors affecting communication

13. Why do we need QoS?
As multimedia becomes more widespread, strain on network increases!
Networks provide insufficient QoS for distribution of multimedia.
Ethernet (wired or wireless) is best effort
Collisions, data loss, congestion, etc.
For some multimedia applications, synchronization is vital.

14. QoS Managers
Software that runs on network nodes which have two main functions:
QoS negotiation: get requirements from apps and checks feasibility versus available resources.
Admission control: If negotiation succeeds, provides a "resource contract" that guarantees reservation of resources for a certain time.

15. Ways to achieve QoS Buffering (on both ends) Compression
More load on the nodes, but that is okay
Bandwidth Reservation
Resource Scheduling
Traffic Shaping
Flow Specifications
Stream Adaptation

16. Traffic Shaping
Output buffering at the source to keep data flowing smoothly.
Two main algorithms:
Leaky bucket: guarantees that data flows at a constant rate without bursts - completely eliminate bursty traffic.
Token bucket: variation of leaky bucket where tokens are generated to allow for some bursty traffic when bandwidth is unused for a certain period of time.

17. Traffic Shaping

18. Flow specifications RFC 1363 defines QoS parameters: Bandwidth
Latency and jitter constraints
Data loss limits
Token bucket size
Instructor’s Guide for Coulouris, Dollimore and Kindberg Distributed Systems: Concepts and Design Edn. 3 © Pearson Education 2001

19. Stream Adaptation Adjust the data flow based on resource availability.
Scaling
Scale down content at the source to reduce bandwidth required:
Audio: reduce the rate of audio sampling or dropping channels
Video: reduce resolution, number of pixels, change compression algorithm, color depths, color spaces, and combinations.
Filtering
One target asks the source to reduce quality for all the clients, even if some can handle higher quality.
Suitable for more than one simultaneous target and guarantees the same QoS for all the targets

20. Applications of DMMS Digital Libraries Distance learning
Teleconferencing
Video on Demand (VoD) & Video on Reservation (VoR)
Pay Per View
Audio Streaming
Video Streaming
E-commerce
P2PTV

21. Voddler Video on Demand and Pay Per View Long movies
Requires high bandwidth
Hybrid P2P distribution network

22. Voddler

23. YouTube, Platform Apache Python Linux MySQL Psyco
lighttpd for video instead of Apache, because of overheads

24. YouTube, Serving Video
Each video hosted by a mini-cluster. Each video is served by more than one machine.
Most popular content is moved to a CDN (content delivery network)
Less popular content (1-20 views per day) uses YouTube servers in various proper sites

25. YouTube, Data Center Strategy
Used manage hosting providers at first. Living off credit cards so it was the only way.
Managed hosting can't scale with you. You can't control hardware or make favorable networking agreements.
So they went to a colocation arrangement. Now they can customize everything and negotiate their own contracts.
Videos come out of any data center. Not closest match or anything. If a video is popular enough it will move into the CDN.

26. Questions? 26