1. Multimedia/Real-Time Prashanth Reddy

2. Multimedia and Real-Time Audio and Video – Continuous Media (CM) Graphics – Discrete media CM –High data rates –Timing requirements Soft real-time applications

3. 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

4. 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

5. 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

6. 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

7. DWS contd…

8. 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

9. Split-level scheduling contd…

11. 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

12. 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”

13. Performance Evaluation

14. Performance Evaluation contd…

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

16. 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

17. MediaNet Architecture Video description, location, & resource info User’s desired stream & adaptation prefs Global scheduling service publish subscribe Video source Video player schedules feedback from MediaNet’s website

18. 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

19. Operations Op frm n IntervalFrame size Other attributes Fixed location? Transitional? … frm 1 … from MediaNet’s website

20. Example User Specification 1.0 0.3 0.1 Vid Prio*Vid Prio* Drop PB Prio*User Drop B Prio*User Prio*User pcS pcD UtilityCMN

21. Scheduling

22. Scheduling contd…

23. 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

24. 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

25. 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

26. 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

27. 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 clipBandwidth Requirements Frame rateI+P+BI+PI 30 fps145 KB/s88 KB/s27 KB/s

28. Results No adaptationPriority-based frame dropping Local, proactive frame droppingMediaNet

29. Multi-User Performance

30. Multi-User Performance contd…

31. B frame dropping op

32. Multi-User Performance contd… B frame dropping op

33. 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

34. 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

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

36. Thank You