CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara...

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CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011

Transcript of CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara...

Page 1: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

CS 414 - Spring 2011

CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6)

Klara Nahrstedt

Spring 2011

Page 2: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Administrative

MP3 going on

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Page 3: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Outline Example of Multimedia File System - Symphony

Two-level Architecture Cello Scheduling Framework at Disk Management level Buffer Subsystem Video Module Caching

Example of Industrial Multimedia File System – Tiger Shark System

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Page 4: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Example Multimedia File System (Symphony)

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Source: P. Shenoy et al, “Symphony: An Integrated Multimedia File System”, SPIE/ACM MMCN 1998

System out of UT Austin Symphony’s Goals:

Support real-time and non-real time request Support multiple block sizes and control over their

placement Support variety of fault-tolerance techniques Provide two level metadata structure that all type-

specific information can be supported

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Design Decisions

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Two Level Symphony Architecture

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Resource Manager: • Disk Schedule System (called Cello) that uses modified SCAN-EDF for RT Requests and C-SCAN for non-RT requests as long as deadlines are not violated• Admission Control and Resource Reservation for scheduling

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Disk Subsystem Architecture

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Service Manager : supports mechanisms for efficient scheduling of best-effort, aperiodic real-time and periodic real-time requestsStorage Manager: supports mechanisms for allocation and de-allocation of blocksOf different sizes and controlling data placement on the diskFault Tolerance layer: enables multiple data type specific failure recovery techniquesMetadata Manager: enables data types specific structure to be assigned to files

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Cello Disk Scheduling Framework

CS 414 - Spring 2011Source: Prashant Shenoy, 2001

Page 9: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Class-Independent Scheduler

CS 414 - Spring 2011Source: Prashant Shenoy, 2001

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Class-Specific Schedulers

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Page 11: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Validation: Symphony’s scheduling system (Cello)

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Source: Shenoy Prashant, 2001

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Buffer Subsystem

Enable multiple data types specific caching policies to coexist

Partition cache among various data types and allow each caching policy to independently manage its partition

Maintain two buffer pools: a pool of de-allocated buffers pool of cached buffers.

Cache pool is further partitioned among various caching policies Buffer that is least likely to be accessed is stored at the head of the

list. (Examples of caching policies for each cache buffer: LRU, MRU)

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Page 13: CS 414 - Spring 2011 CS 414 – Multimedia Systems Design Lecture 30 – Media Server (Part 6) Klara Nahrstedt Spring 2011.

Buffer Subsystem (Protocol)

Receive buffer allocation request Check if the requested block is cached.

If yes, it return the requested block If cache miss, allocate buffer from the pool of de-allocated buffers and

insert this buffer into the appropriate cache partition

Determine (Caching policy that manages individual cache) position in the buffer cache If pool of de-allocated buffers falls below low watermark, buffers are

evicted from cache and returned to de-allocated pool Use TTR (Time To Reaccess) values to determine victims

TTR – estimate of next time at which the buffer is likely to be accessed

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Video Module

Implements policies for placement, retrieval, metadata management and caching of video data

Placement of video files on disk arrays is governed by two parameters: block size and striping policy. supports both fixed size blocks (fixed number of bytes) and

variable size blocks (fixed number of frames) uses location hints so as to minimize seek and rotational latency

overheads

Retrieval Policy: supports periodic RT requests (server push mode) and aperiodic

RT requests (client pull mode)

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Video Module (Metadata Management)

To allow efficient random access at byte level and frame level, video module maintains two-level index structure First level of index ,

referred to as frame map, maps frame offset to byte offset

Second level, referred to as byte map, maps byte offset to disk block locations

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Symphony Caching Policy

Interval-based caching for video module LRU caching for text module

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IBM Multimedia File System

The Tiger Shark File System Roger L. Haskin, Frank B. Schmuck IBM Journal of Research and Development, 1998

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The newer MM Filesystems:Classes of requests Tiger Shark filesystem defines different types of classes to FS

requests. minimum needed is 2 classes.

Legacy Requests Read/Write data for small files, not needed quickly at the NIC

High-Performance Requests Read data for large likely-contiguous files that needs to be quickly dumped to

the nic (network interface control)

This is similar to our newer networking paradigm “not all traffic is equal”

Unaddressed question that I had: Can we take the concept of discardability and apply it to filesystems?

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Classes of Requests

Tiger Shark Real-time Class

Real-time class is fine grained into subclasses, because Tiger Shark has

Resource Reservation Admission Control

If the controllers and disks cannot handle the predicted load then the request is denied.

Legacy Class Also has a legacy interface for old filesystem access

interfaces.

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Quantization, and Scheduling Optimizations

"Deadline Scheduling" instead of elevator algorithms.

Blocksize is 256KB (default), Normal AIX uses 4KB size.

Tiger Shark will "chunk" contiguous block reads better than the default filesystems to work with its large blocksize.

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Streamlining of operations to get data from platter to NIC. Running daemon that pre-allocates OS resources

such as buffer space, disk bandwidth and controller time.

Not a hardware-dependent solution. Even though it does not have shared memory hardware,

Tiger Shark copies data from the disks into a shared memory area. Essentially this is a very large extension of the kernel's disk block cache.

VFS layer for Tiger Shark intercepts repeated calls and uses the shared memory area, therefore saving kernel memcopys on subsequent requests.

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Platter Layout and Scaling Optimizations for Contiguous Streaming Striping across a maximum of 65000

plattersStriping method unspecified, looks like it is

flexible and extended to include redundancy if desired.

All members of a block group contiguousattempts to keep the block groups contiguous.

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Seeking Optimizations

Byte Range Locking. Allows multiple clients to access different

areas of a file with real-time guarantees if they don't step on each other.

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Current Research and Future Directions Tiger Shark gives us Filesystem QoS. But can we do better by integrating VBR/ABR into the

system? Replication and redundancy are always an issue, but

not addressed in this scope. If it is a software-based system such as Tiger Shark,

where in the OS should we put these optimizations? (Kernel, Tack-On Daemon, Middleware)

Legacy disk accesses have a huge cost in both of these systems, how can we minimize?

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Tiger Shark Final Thoughts Adds QoS guarantees to current disk interface

architectures

Built to be extensible to more than just MM disk access. But definitely optimized for multimedia.

Designed to serve more concurrent sessions out of a multimedia server BUT there is still kernel bottleneck for the initial block

load. Better suited to multiple concurrent access than

EXT3NS

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Conclusion

The data placement, scheduling, block size decisions, caching, concurrent clients support, buffering, are very important for any media server design and implementation.

Next Lecture – we discuss Multimedia CPU Scheduling

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