Multimedia/Real-Time

Prashanth Reddy

Multimedia and Real-Time

• Audio and Video – Continuous Media (CM)

• Graphics – Discrete media

• CM– High data rates– Timing requirements

• Soft real-time applications

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

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

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

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) <= t

• Workahead processes - real-time processes that have pending messages but not critical

DWS contd…

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

Split-level scheduling contd…

Split-level scheduling contd…

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

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”

Performance Evaluation

Performance Evaluation contd…

Summary

• Proper scheduling through Split-level scheduling and usage of shared memory

• MMS – low-overhead IPC mechanism

• Reduced user-kernel interactions

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

MediaNet Architecture

Video description,location, &

resource info

User’s desiredstream &

adaptation prefs

Globalscheduling

service

publish

subscribe

Video source

Video player

schedules

feedback

from MediaNet’s website

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

Operations

Op

frmn

IntervalFrame sizeOther attributes• Fixed location?• Transitional?

…

frm1

…

from MediaNet’s website

Example User Specification

1.0

0.3

0.1

Vid

Prio*Vid

Vid Prio*DropPB

Prio* User

DropB

Prio* User

Prio* UserpcS

pcS

pcS

pcD

pcD

pcD

Utility CMN

Scheduling

Scheduling contd…

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

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

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

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

Experiments

• Conducted on 8 850 MHz PIII’s, 512 MB RAM, 100 Mb/s Ethernet, Red Hat Linux 7.1 using a “bowtie” topology:

MPEG clip Bandwidth Requirements

Frame rate I+P+B I+P I

30 fps 145 KB/s 88 KB/s 27 KB/s

Results

No adaptation Priority-based frame dropping

Local, proactive frame dropping MediaNet

Multi-User Performance

Multi-User Performance contd…

Multi-User Performance contd…

B frame dropping op

Multi-User Performance contd…

B frame dropping op

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

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

Acknowledgements

• Some of the slides have been taken from MediaNet’s website: http://www.cs.umd.edu/projects/medianet/

Thank You