Transcript Distributed Multimedia Systems

Distributed Multimedia
Systems
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Resource Management
Stream Adaptation
Case Study
The Tiger Video file server
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Resource Management
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Resource Scheduling
To provide Quality of Service (Qos) to
an application not only system must
have sufficient resource
(performance), it also needs to make
these resource available to an
application when they are needed
(scheduling).
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Resource Scheduling
Fair Scheduling
 Real-time Scheduling
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Fair Scheduling
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If several streams compete for a same
resource it is necessary to consider
fairness and to prevent ill behaved
streams taking too much bandwidth.
Round robin method is used on bit by
bit basis, which provides more fairness
with respect to varying packet sizes and
arrival times.
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Real-time Scheduling
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The Scheduling algorithms assigns CPU
time slots to a set of processes in a
manner that ensures that they complete
their tasks on time.
Earliest- deadline first (EDF).
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Stream Adaptation
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Adjustment in Qos
Droping a piece of information (audio)
Dropouts in video stream MPEG
We Use scaling methods for dropouts.
For video files we use the following
scaling methods or combination of it.
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Video Scaling methods
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Temporal Scaling
Spatial Scaling
Frequency Scaling
Amplitudinal Scaling
Color space Scaling
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Scaling
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Temporal Scaling
reduces the resolution of video stream
in the time domain by decreasing the
number of video frames transmitted
with in a interval.
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Scaling
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Spatial Scaling
reduces the number of pixels of each
image in a video stream.
Frequency Scaling
modifies compressed algorithm applied
to a image.
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Scaling
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Amplitudinal Scaling
Reduces the color depth of each image
pixel
Color space Scaling
Reduces the number of entities in the
color space
color -> gray scale
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Filtering
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Scaling modifies the stream of source it
is not suitable for applications that
involve several receivers: if bottleneck
occurs on the route of one target, This
target sends Scale-down message to
the source and all targets receive the
degraded quality,although some do not
require.
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Filtering
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Filtering is a method that provides the
best possible quality of service to each
target applying.
Filtering requires that a stream be
partitioned into a set of hierarchical sub
streams, each adding a higher level of
quality.
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Filtering
Targets
Source
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Case Study
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A video storage system that supplies
multiple real time video streams
simultaneously is seen as an important
system component to support
consumer-oriented multimedia
applications.
Tiger video file server developed by
Microsoft research Labs.
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Case Study : The Tiger video
file server
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Design goals
Architecture
Storage organization
Distributed schedule
Network support
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Design Goals
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Video on demand for a large number of
users
Quality of service
Scalable and distributed
Low cost hardware
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Architecture
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The Cub Computers are identical PC’s
with same number of standard Hard
disk drives attached to each. They are
equipped with ethernet and ATM
network cards. The Controller is another
PC it handles the client requests and
manages the work schedule of the curb.
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Architecture
Controller
Controller
Low-bandwidth network
0…n+1 1…n+2 2…n+3
Cub 0 Cub 1 Cub 2
ATM Switching network
Video Distribution to clients
n…2n+1
Cub n
start/
Stop requests
From clients
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Storage organization
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Video data is a large file in order to share the
load its distributed among the disks attached
to the cubs.
A movie is divided into blocks ( 1sec ->
0.5MB so a 2 hr movie has app. 7000) Movie
can start on any disk whenever highest
numbered disk is reached, the movie is
wrapped around so that next block disk 0 is
in process.
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Distributed Schedule
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Scheduling workload for the cubs.
Schedule is organized as list of slots
Each slot rep. Work must be done to
play one block of movie
read it from relevant disk
transfer it to ATM network.
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Network support
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The blocks of each movie are simply
passed to the ATM network by the cubs
that hold them, together with the
address of the relevant client.
Client needs sufficient buffer storage to
hold two buffer locations 1 is playing
the video and other is arriving from the
network.
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Problem 1
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Outline the design of a QoS manager to
enable desktop Computers connected
by an ATM network to support several
concurrent multimedia applications.
Define an API for your QoS manager,
giving the main operations with their
parameters and results.
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Problem 2
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In order to specify the resource
requirements software components that
process multimedia data, we need
estimates for their processing loads.
How can this information can be
obtained without undue effort?
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Problem 3
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The Tiger schedule is potentially a large
data structure that changes frequently,
but each cub needs an up-to-date
representation of the portions it is
currently handling. Suggest a
mechanism for the distribution of the
schedule to the cubs.
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Problem 4
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When Tiger is operating with a failed
disk or cub, secondary data blocks are
used in place of missing primaries.
Secondary blocks are n times smaller
than primaries ( where n is the
decluster factor), how does the system
accommodate this variability in block
size?
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