Multimedia/Real-Time

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Multimedia/Real-Time

• Prashanth Reddy

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Multimedia and Real-Time

• Audio and Video Continuous Media (CM)
• Graphics Discrete media
• CM
• High data rates
• Timing requirements
• Soft real-time applications

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Problems

• Traditional OSs do not provide good support
• Schedulers
• Round Robin, Priority scheduling
• No sense of urgency
• Large number of user-kernel level interactions
• Efficient usage of resources
• Varying demands
• Delays, jitter

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Papers

• Scheduling and IPC Mechanisms for Continuous
  Media
• New scheduling and IPC mechanisms
• Split-level scheduling
• User-level and kernel-level scheduler
• Use shared memory
• Memory mapped streams
• Shared memory FIFO

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Papers

• User-specified Adaptive Scheduling in a Streaming
  Media Network
• Deliver data in resource-limited, small-scale
  environments
• Meet the preferences and demands of the users
• MediaNet a distributed stream processing system

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Deadline/Workahead Scheduling

• Each message has a logical arrival time l(m)
• Each real-time process has a fixed logical delay
  bound
• A real-time process is critical at time t if
  l(m) lt t
• Workahead processes - real-time processes that
  have pending messages but not critical

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DWS contd
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Split-level CPU scheduling

• Combines the advantages of thread and LWPs
• Minimizes user/kernel interactions
• Also prioritizes LWPs in different VASs correctly
• Kernel level scheduler and user level scheduler
  communicate through shared memory

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Split-level scheduling contd
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Split-level scheduling contd
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Memory Mapped Streams

• CM data must be moved to/from kernel
• Components
• Control and Synchronization
• Data location transfer
• Data transfer
• Requires user/kernel interaction in one or more
  of the above components

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MMS contd

• A shared memory FIFO
• Uses shared memory for control and
  synchronization
• Uses shared memory to hold data location and the
  data
• Mechanisms
• Statically shared pages of physical memory
• Fixed range of virtual pages, mapped dynamically
• Array of message descriptors

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Performance Evaluation
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Performance Evaluation contd
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Summary

• Proper scheduling through Split-level scheduling
  and usage of shared memory
• MMS low-overhead IPC mechanism
• Reduced user-kernel interactions

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User-specified Adaptive Scheduling in a Streaming
Media Network

• MediaNet a distributed stream processing system
• Users can specify how the system should adapt
• Uses local and global resource scheduling
• Adapts without resource reservation

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MediaNet Architecture
Video source
Users desired stream adaptation prefs
schedules
Global scheduling service
Video player
subscribe
feedback
Video description, location, resource info
publish
from MediaNets website
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Specifications

• Continuous Media Network (CMN)
• Directed acyclic graph of operations
• frame dropping, transcoding, compression and
  decompression etc.
• User specification
• One or more CMNs, each with associated utility
  value
• Goal Maximize users utility while utilizing the
  network efficiently

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Operations
Op
frm1


frmn
Interval
Frame size

• Other attributes
• Fixed location?
• Transitional?

from MediaNets website
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Example User Specification
Utility
CMN
Vid
Prio
User
1.0
pcS
pcD
Prio
Vid
Drop B
Prio
User
0.3
pcS
pcD
Vid
Prio
Drop PB
Prio
User
0.1
pcS
pcD
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Scheduling
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Scheduling contd
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Implementation

• Global scheduling service
• implemented on a single node
• eventually hierarchical
• Local, per-node schedulers
• monitor and report available bandwidth
  eventually CPU memory usage
• implement local CMNs
• Global scheduler reconfigures schedules on-line

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Local Scheduler

• Implement the CMN given by the GS
• Must correctly reconfigure on-line
• Report monitoring info back to GS
• Implemented in Cyclone
• Type-safe, C-like language
• One component per operation, dynamically
  reconfigurable
• Uses TCP for send/receive

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Monitoring

• Monitor available bandwidth
• Keep track of TCP throughput, attempted vs.
  actual bandwidth
• Send regular reports to global scheduler
• Too pessimistic
• creep bandwidth estimate additively to
  optimistically attempt higher utility configs

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Reconfiguration

• New configuration is applied in parallel with the
  current configuration
• Old operations are flushed along the dataflow
  path
• New operations are enabled when all old ones are
  flushed on a particular node
• Challenges
• Rapid reconfiguration
• Low disruption to stream

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Experiments

• Conducted on 8 850 MHz PIIIs, 512 MB RAM, 100
  Mb/s Ethernet, Red Hat Linux 7.1 using a bowtie
  topology

MPEG clip Bandwidth Requirements Bandwidth Requirements Bandwidth Requirements
Frame rate IPB IP I
30 fps 145 KB/s 88 KB/s 27 KB/s
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Results
No adaptation
Priority-based frame dropping
Local, proactive frame dropping
MediaNet
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Multi-User Performance
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Multi-User Performance contd
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Multi-User Performance contd
B frame dropping op
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Multi-User Performance contd
B frame dropping op
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Summary

• Application-specific QoS via user specs
• High network utilization and per-user utility via
  global scheduling
• Share resources between flows in a multicast-like
  manner, but generalized to CMNs
• Utilize multiple, redundant paths
• Intelligently place operations to reduce network
  utilization
• Adapts to resource availabilities on-line

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Conclusion

• Split-level scheduling
• Tight coupling between user-level and
  kernel-level schedulers
• Difficult to employ multiple scheduling policies
• Scalability
• Hierarchical global scheduling service
• Automate setting utility values

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Acknowledgements

• Some of the slides have been taken from
  MediaNets website http//www.cs.umd.edu/projects
  /medianet/

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Thank You