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Characteristics of multimedia data
Quality of service management
Resource management
Stream adaptation
Case study: Tiger video file server

Distributed Multimedia Systems

Distributed Multimedia Systems

 Applications:
   – non-interactive: net radio and TV, video-on-demand, e-learning, ...
   – interactive: voice &video conference, interactive TV, tele-medicine,
     multi-user games, live music, ...

Characteristics of multimedia applications

 Large quantities of continuous data
 Timely and smooth delivery is critical
   – deadlines
   – throughput and response time guarantees
 Interactive MM applications require low round-trip delays
 Need to co-exist with other applications
   – must not hog resources
 Reconfiguration is a common occurrence
   – varying resource requirements
 Resources required:
   –   Processor cycles in workstations
   –   and servers
   –   Network bandwidth (+ latency)           At the right time
   –   Dedicated memory                        and in the right quantities
   –   Disk bandwidth (for stored media)
Application requirements

 Network phone and audio conferencing
   – relatively low bandwidth (~ 64 Kbits/sec), but delay times must be short ( <
     250 ms round-trip)

 Video on demand services
   – High bandwidth (~ 10 Mbits/s), critical deadlines, latency not critical

 Simple video conference
   – Many high-bandwidth streams to each node (~1.5 Mbits/s each), high
     bandwidth, low latency ( < 100 ms round-trip), synchronised states.

 Music rehearsal and performance facility
   – high bandwidth (~1.4 Mbits/s), very low latency (< 100 ms round trip), highly
     synchronised media (sound and video < 50 ms).

System support issues and requirements

 Scheduling and resource allocation in most current OS’s
  divides the resources equally amongst all comers (processes)
   – no limit on load
   – \ can’t guarantee throughput or response time

 MM and other time-critical applications require resource
  allocation and scheduling to meet deadlines
   – Quality of Service (QoS) management
        Admission control:     controls demand
        QoS negotiation:       enables applications to negotiate admission and
        Resource management:   guarantees availability of resources for
                                admitted applications
   – real-time processor and other resource scheduling

Characteristics of typical multimedia streams

                           Data rate                 Sample or frame
                         (approximate)               size   frequency

  Telephone speech             64 kbps               8 bits   8000/sec
  CD-quality sound            1.4 Mbps              16 bits 44,000/sec
  Standard TV video           120 Mbps     up to 640 x 480      24/sec
  (uncompressed)                           pixels x 16 bits
  Standard TV video           1.5 Mbps             variable      24/sec
  (MPEG-1 compressed)
  HDTV video            1000–3000 Mbps up to 1920 x 1080      24–60/sec
  (uncompressed)                          pixels x 24 bits
  HDTV video                10–30 Mbps             variable 24–60/sec
  MPEG-2 compressed)
     Typical infrastructure components for multimedia applications
   Figures 15.4 & 15.5
                                                      PC/workstation                                                   PC/workstation    Window
       : multimedia stream                                                                                                               system
                                      Camera                                         K
White boxes represent media                            A                                                              G             H
processing components, many                                Codec                                                       Codec
of which are implemented
                                                       B                             L
in software, including:               Microphones
 codec: coding/decoding filter                                                    Network
 mixer: sound-mixing component        Screen     C                                connections                        Video file system    Video
                                                            D                        M                                                    store
                                                 Window system

                       Component          Bandwidth                               Latency       Loss rate   Resources required
                             Camera       Out:       10 frames/sec, raw video                   Zero
                                                     640x480x16 bits

                        Codec application involves multiple concurrent ms CPURAM 100 ms; the
                          This In:
                                      10 frames/sec, raw video Interactive Low
                                      MPEG-1 stream
                                                                                       processes in
                                                                                    10 Mbytes

                          PCs In:
                       B Mixer        2 44 kbps audio          Interactive Very low 1 ms CPU each 100 ms;
                                          Out:       1 44 kbps audio                                        1 Mbytes RAM
                        Window applications may also Interactive Low concurrently 100 ms;
                       H  Other In:   various                  be running 5 ms CPU each on the
                         system Out:  50 frame/sec framebuffer            5 Mbytes RAM
                          same computers
                       K     Network    In/Out:      MPEG-1 stream, approx.       Interactive   Low         1.5 Mbps, low-loss
                             connection              1.5 Mbps                                               stream protocol
                        Network all share processing and network low 44 kbps, very low-loss
                          They In/Out: Audio 44 kbps    Interactive Very
                             connection                                                                     stream protocol
Quality of service management

 Allocate resources to application processes
   – according to their needs in order to achieve the desired quality of multimedia

 Scheduling and resource allocation in most current OS’s
  divides the resources equally amongst all processes
   – no limit on load
   – \ can’t guarantee throughput or response time

 Elements of Quality of Service (QoS) management
   – Admission control:       controls demand
   – QoS negotiation:         enables applications to negotiate admission and
   – Resource management: guarantees availability of resources for
                              admitted applications
   – real-time processor and other resource scheduling
The QoS manager’s task

    Ad mi ssi on co ntro l                                                                      QoS ne goti ation
                               Application c omponents s pecify their QoS
                                     requirements to QoS manager
                                                        Fl ow spec.
                               QoS manager ev aluatesnew requirements
                                       agains t the av ailable res ources.
                                                  Suff icient?
                                             Yes                   No

        Reserv e the reques ted res ources            Negotiate reduced res ource prov ision with application.
                Re sou rce con tract                                     Yes                 No
           Allow application to proceed
                                                                             Do not allow application to proceed

        Application runs with resources as              Application notif ies QoS manager of
              per res ourc e contract                    inc reas ed res ource requirements

QoS Parameters

                   The RFC 1363 Flow Spec
  – rate of flow of multimedia data
                                             Protocol version
Latency                                 Maximum transmission unit
  – time required forBandwidth:        Token bucket rate
                      the end-to-end transmission of a single data element
  Jitter                               Token bucket size
                                        Maximum transmission rate   maximum rate
       variation in latency :– dL/dt
                                          Minimum delay noticed     acceptable latency
                                                                    acceptable jitter
Loss rate                                Maximum delay variation
                                                 Loss sensitivity   percentage per T
  – the proportion of data elements that can be dropped or          delivered late
                                                                    maximum consec-
                            Loss:          Burst loss sensitivity
                                                                            utive loss
                                                  Loss interval     T
                                           Quality of guarantee     value

                                       Figure 15.8 The RFC 1363 Flow Spec

                                                               Protocol version
Managing the flow of multimedia data transmission unit
                                                              Token bucket rate
                                          Bandwidth:                                    burstiness
                                                              Token bucket size

 Flows are variable
                                                          Maximum transmission rate   maximum rate
                                                            Minimum delay noticed     acceptable latency
   – video compression methods such as MPEG (1-4)delay variation onacceptable jitter
                                                           are based
                                                   Loss sensitivity     percentage per T
     similarities between consecutive frames
                                        Loss:    Burst loss sensitivity
                                                                        maximum consec-
                                                                                 utive loss
   – can produce large variations in data rate       Loss interval      T
                                                             Quality of guarantee     value

 Burstiness
   – Linear bounded arrival process (LBAP) model:
        maximum flow per interval t = Rt + B          (R = average rate, B = max. burst)
   – buffer requirements are determined by burstiness
   – Latency and jitter are affected (buffers introduce additional delays)

 Traffic shaping
   – method for scheduling the way a buffer is emptied

Traffic shaping algorithms – leaky bucket algorithm

             (a) Leaky bucket

                          process 1

                          process 2

analogue of leaky bucket:
   – process 1 places data into a buffer in bursts
   – process 2 in scheduled to remove data regularly in smaller amounts
   – size of buffer, B determines:
       maximum permissible burst without loss
       maximum delay
Traffic shaping algorithms – token bucket algorithm

                                            (b) Token bucket

                                                 process 1
tokens: permits to place x bytes                                    process 2
into output buffer                                   process 3     Token generator

Implements LBAP
    – process 1 delivers data in bursts
    – process 2 generates tokens at a fixed rate
    – process 3 receives tokens and exploits them to deliver output as quickly as it
      gets data from process 1
Result: bursts in output can occur when some tokens have accumulated
Admission control

Admission control delivers a contract to the application
  guaranteeing:                        For each network connection:
   For each computer:                                                  bandwidth
         cpu time, available at specific intervals                    latency
         memory                                              For disks, etc.:

Before admission, it must assess resource requirements and
  reserve them for the application
   – Flow specs provide some information for admission control, but not all - assessment
     procedures are needed
   – there is an optimisation problem:
         clients don't use all of the resources that they requested
         flow specs may permit a range of qualities
   – Admission controller must negotiate with applications to produce an acceptable result

Resource management

                                                      e.g. for each computer:
 Scheduling of resources                              cpu time, available at specific intervals
  to meet the existing guarantees:                     memory
     Fair scheduling allows all processes some portion of the resources based on
EDF scheduling
Each task specifies a deadline T and CPU seconds S to the scheduler for each
           E.g. round-robin scheduling (equal turns), fair queuing (keep queue lengths equal)
                                          scheduler schedules the task to delivery of
work item (e.g. video frame). EDFMM because there are deadlines for therun at least
           not appropriate for real-time
             before T (and pre-empts it after S if it hasn't yielded).
S seconds data
It has been shown that EDF will find a schedule that meets the deadlines, if
     Real-time scheduling traditionally used in special OS for system control
        applications e.g. S is likely schedulers must ensure that tasks are
one exists. (But for- MM,avionics. RTto be a millisecond or so, and there is a
         that the by a scheduled have
danger completedscheduler may time. to run so frequently that it hogs the cpu).
          Real-time MM requires real-time scheduling with very frequent deadlines.
Rate-monotonic scheduling assigns priorities to tasks according to tasks
        Suitable types of scheduling are:
according to their rate of data throughput (or workload). Uses less CPU for
             Earliest deadline first (EDF)
scheduling decisions. Has been shown to work well where total workload is <
69% of CPU.

Scaling and filtering


              High bandwidth
              Medium bandwidth
              Low bandwidth

 Scaling reduces flow rate at source
   – temporal: skip frames or audio samples
   – spatial: reduce frame size or audio sample quality

 Filtering reduces flow at intermediate points
   – RSVP is a QoS negotiation protocol that negotiates the rate at each
     intermediate node, working from targets to the source.
QoS and the Internet

 Very little QoS in the Internet at present
   – New protocols to support QoS have been developed, but their implementation
     raises some difficult issues about the management of resources in the

 IPv6 header layout
   – Network resource reservation
 Version (4 bits)Priority (4bits) of reservations label (24 b its)
   – Doesn’t ensure enforcement
    Payload leng th (16 bits)              Next h eader (8bits) Hop limit (8bits)
   – Real time data transmission over IP ad dress
                                    (1 28 bits)
 need to avoid adding undesirable complexity to the Internet
 IPv6 has some hooks for it
                               Destination ad dress
                                    (1 28 bits)
Case Study Tiger Video File server

 Microsoft NetShow Video file server
 Design goals
   –   Video on demand for a large number of users
   –   Quality of service
   –   Scalable and distributed                                    Clients
   –   Low cost hardware
   –   Fault tolerant

Tiger architecture

   Storage organization
    –   Striping
    –   Mirroring

   Distributed schedule
   Tolerate failure of any single computer or disk
   Network support
   Other functions
    –   pause, stop, start

  Tiger hardware configuration

            low-bandwidth network

             0   n+1      1   n+2    2    n+3       3      n+4           n   2n+1

              Cub 0       Cub 1       Cub 2             Cub 3            Cub n

                                     ATM switching network

   Cubs and controllers                                                     Start/Stop
   are standard PCs                                                     requests from clients
                                    video distribution to clients

  Each movie is stored in 0.5 MB blocks (~7000) across all disks in the order of the disk
     numbers, wrapping around after n+1 blocks.
  Block i is mirrored in smaller blocks on disks i+1 to i+d where d is the decluster factor
     (typically 4 - 8)
Distributed Schedule

 Scheduling of workload of cubs
   – Slots
       Work required to serve on block of a movie
       One slot for each viewer (client)

    Tiger schedule

                           2                                 1                 block service           0
                                    block play time T                              time t

             slot 0        slot 1      slot 2      slot 3             slot 4        slot 5         slot 6        slot 7
                                              viewer  client           viewer state:
            viewer 4        free       free       viewer 0        viewer 3         viewer 2        free        viewer 1
              state                                 state           state            state                       state

       Stream capacity of a disk = T/t (typically ~ 5)                         Viewer state: Network address of client
       Stream capacity of a cub with n disks = n x T/t                                        FileID for current movie
                                                                                              Number of next block
               Cub algorithm:
                                                                                              Viewer's next play slot
               1.     Read the next block into buffer storage at the Cub.
               2.     Packetize the block and deliver it to the Cub’s ATM network controller with the
in time t             address of the client computer.
               3.     Update viewer state in the schedule to show the new next block and play sequence
                      number and pass the updated slot to the next Cub.
               4.     Clients buffer blocks and schedule their display on screen.

Tiger performance and scalability

1994 measurements:
   – 5 x cubs: 133 MHz Pentium Win NT, 3 x 2Gb disks each, ATM
   – supported streaming movies to 68 clients simultaneously without lost
   – with one cub down, frame loss rate 0.02%

1997 measurements:
   – 14 x cubs: 4 disks each, ATM network
   – supported streaming 2 Mbps movies to 602 clients simultaneously with
     loss rate of < .01%
   – with one cub failed, loss rate <.04%
The designers suggested that Tiger could be scaled to 1000
  cubs supporting 30,000 clients.

 MM applications and systems require new system
  mechanisms to handle large volumes of time-dependent data
  in real time (media streams).
 The most important mechanism is QoS management, which
  includes resource negotiation, admission control, resource
  reservation and resource management.
 Negotiation and admission control ensure that resources are
  not over-allocated, resource management ensures that
  admitted tasks receive the resources they were allocated.
 Tiger file server: case study in scalable design of a stream-
  oriented service with QoS.


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