Distributed Multimedia Systems 1

Examples of DMMS And more!

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." http://encyclopedia.jrank.org/articles/pages/6729/Distributed-Multimedia-Systems.html

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

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

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

Typical infrastructure components for multimedia applications

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

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

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)

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

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.

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.

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

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.

Traffic Shaping

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

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

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

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

Voddler http://en.wikipedia.org/wiki/File:P2ptv.PNG

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

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

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.

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