DistOS 2014W Lecture 23: Difference between revisions
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=== | '''Presentations''' | ||
===Distributed Shared Memory Systems - Mojgan=== | |||
* Introduction to DSM systems | |||
* Advantages and Disadvantages | |||
* Classification of DSM systems | |||
* Design considerations | |||
* Examples of DSM systems | |||
- OpenSSI | |||
- Mermaid | |||
- MOSIX | |||
- DDM | |||
===Survey: Fault Tolerance in Distributed File System - Mohammed=== | |||
* Abstract | |||
* Introductions | |||
** About fault tolerance in any distributed system. Comparison between different file systems. | |||
** Whats more suitable for Mobile based systems. | |||
** Why satisfaction high for fault tolerance is one of the main issues for DFS's ? | |||
* Replication and fault tolerance | |||
** What is the Replica and Placement policy? What is the synchronization? What is its benefit? | |||
- Synchronous Method | |||
- Asynchronous Method | |||
- Semi-Asynchronous Method | |||
* Cache consistency and fault tolerance | |||
** What is the cache? What is its benefit? Cache consistency? | |||
- Write only Read Many (WORM) | |||
- Transactional Locking - Read and write locks | |||
- Leasing | |||
* Example DFS mentioned in the paper | |||
** Google File Systems | |||
** HDFS | |||
** MOOSEFS | |||
** iRODS | |||
** GlusterFS | |||
** Lustre | |||
** Ceph | |||
** PARADISE for mobile | |||
* Conclusion | |||
===Survey on Control Plane Frameworks for Software Defined Networking - Sijo=== | |||
* Introduction | |||
** Traditional Networks - Control Plane and Forwarding Plane | |||
** Software Defined Networking | |||
- Proposes decoupling of layers into independent layers | |||
- Network entities or nodes are specialized elements which does the forwarding | |||
- Control applications works on the logical view of the network provided by the controller without having to worry about | |||
managing state distribution, topology discovery etc. | |||
* Theme, Argument Outline | |||
- Need for using distributed systems design principles, tools in SDN controller design to achieve scalability and reliability | |||
* Controller Platforms | |||
- Centralized and Distributed approaches | |||
- Identify the need to use in controller platforms | |||
- For centralized it started with NOX - Maestro - Beacon - Floodlight - POX - OpenDayLight | |||
- For Distributed : ONIX - Hyperflow - YANC - ONOS | |||
- Leverage parallel processing capabilities | |||
* In detail about two systems: | |||
** ONIX | |||
** ONOS | |||
* References | |||
===Metadata management in Distributed File System - Sandarbh=== | |||
* What is metadata? | |||
- Defined by bare-minimum functions for MDS (Metadata Server) | |||
- Monitor the performance of DFS so that it can be used further | |||
- Structure of metadata in Paper | |||
* Why is Metadata management difficult? | |||
- 50% of file operations are metadata operations | |||
- Size of metadata | |||
- Distribute the load evenly across all MDS | |||
- Be able to handle thousands of clients | |||
- Be able to handle file/directory permission change | |||
- Recover data if some MDS goes down | |||
- Be POSIX compliant | |||
- Be able to scale- addition of new MDS shouldn't cause ripples | |||
- Contrasting goals - replication and consistency - Average case improvements vs guaranteed performance for each access | |||
* Static sub-tree partitioning | |||
- Advantage - Clients know which MDS to contact for the file - Prefix caching | |||
- Disadvantage - Directory hot spot formation | |||
* Static hashing based partitioning | |||
- Hash the filename or File identifier and assign it to MDS | |||
- Advantage - Distributes load evenly - Gets rid of hotpsot info | |||
- Disadvantage | |||
* "Don't ask me where your server is" approach | |||
- Ex : Ceph , GlusterFS, OceanStore, Hierarchical Bloom filters, Cassandra | |||
- Responsibilities - Replica management, Consistency, Access control, Recover metadata in case of crash, Talk to each others to handle the load dynamically | |||
* What's not in the slides | |||
- Not focused on replication of metadata | |||
- Semantic based search | |||
* Structure of the survey | |||
- Conventional metadata systems | |||
- No-metadata approach | |||
- Metadata approach of the file systems designed for specific goals 0 GFS, Haystack etcs | |||
- Evolution history | |||
- Comparison within category | |||
- Cover reliability and consistency part | |||
- Summarize learnings with expected trends | |||
===Distributed Stream Processing - Ronak Chaudhari=== | |||
* About Stream processing | |||
- Data streams | |||
- DBMS vs Stream processing | |||
* Applications | |||
- Monitoring applications | |||
- Militia applications | |||
- Financial analysis | |||
- Tracking applications | |||
* Aurora | |||
- Process incoming streams | |||
- It has its own query algebra | |||
- System Model - Query Model - Runtime Architecture | |||
- QOS criteria | |||
- SQuAL - Query algebra | |||
- Aurora GUI | |||
- Challenges in distribute operation | |||
* Aurora vs Medusa | |||
* Medusa | |||
- Architecture | |||
- Addition to Aurora - Lookup and Brain | |||
- Failure detection | |||
- Transfer of processing | |||
- System API | |||
- Load management | |||
- High availability | |||
- Benefits | |||
* References |
Latest revision as of 22:15, 23 April 2014
Presentations
- Introduction to DSM systems
- Advantages and Disadvantages
- Classification of DSM systems
- Design considerations
- Examples of DSM systems
- OpenSSI - Mermaid - MOSIX - DDM
Survey: Fault Tolerance in Distributed File System - Mohammed
- Abstract
- Introductions
- About fault tolerance in any distributed system. Comparison between different file systems.
- Whats more suitable for Mobile based systems.
- Why satisfaction high for fault tolerance is one of the main issues for DFS's ?
- Replication and fault tolerance
- What is the Replica and Placement policy? What is the synchronization? What is its benefit?
- Synchronous Method - Asynchronous Method - Semi-Asynchronous Method
- Cache consistency and fault tolerance
- What is the cache? What is its benefit? Cache consistency?
- Write only Read Many (WORM) - Transactional Locking - Read and write locks - Leasing
- Example DFS mentioned in the paper
- Google File Systems
- HDFS
- MOOSEFS
- iRODS
- GlusterFS
- Lustre
- Ceph
- PARADISE for mobile
- Conclusion
Survey on Control Plane Frameworks for Software Defined Networking - Sijo
- Introduction
- Traditional Networks - Control Plane and Forwarding Plane
- Software Defined Networking
- Proposes decoupling of layers into independent layers - Network entities or nodes are specialized elements which does the forwarding - Control applications works on the logical view of the network provided by the controller without having to worry about managing state distribution, topology discovery etc.
- Theme, Argument Outline
- Need for using distributed systems design principles, tools in SDN controller design to achieve scalability and reliability
- Controller Platforms
- Centralized and Distributed approaches - Identify the need to use in controller platforms - For centralized it started with NOX - Maestro - Beacon - Floodlight - POX - OpenDayLight - For Distributed : ONIX - Hyperflow - YANC - ONOS - Leverage parallel processing capabilities
- In detail about two systems:
- ONIX
- ONOS
- References
Metadata management in Distributed File System - Sandarbh
- What is metadata?
- Defined by bare-minimum functions for MDS (Metadata Server) - Monitor the performance of DFS so that it can be used further - Structure of metadata in Paper
- Why is Metadata management difficult?
- 50% of file operations are metadata operations - Size of metadata - Distribute the load evenly across all MDS - Be able to handle thousands of clients - Be able to handle file/directory permission change - Recover data if some MDS goes down - Be POSIX compliant - Be able to scale- addition of new MDS shouldn't cause ripples - Contrasting goals - replication and consistency - Average case improvements vs guaranteed performance for each access
- Static sub-tree partitioning
- Advantage - Clients know which MDS to contact for the file - Prefix caching - Disadvantage - Directory hot spot formation
- Static hashing based partitioning
- Hash the filename or File identifier and assign it to MDS - Advantage - Distributes load evenly - Gets rid of hotpsot info - Disadvantage
- "Don't ask me where your server is" approach
- Ex : Ceph , GlusterFS, OceanStore, Hierarchical Bloom filters, Cassandra - Responsibilities - Replica management, Consistency, Access control, Recover metadata in case of crash, Talk to each others to handle the load dynamically
- What's not in the slides
- Not focused on replication of metadata - Semantic based search
- Structure of the survey
- Conventional metadata systems - No-metadata approach - Metadata approach of the file systems designed for specific goals 0 GFS, Haystack etcs - Evolution history - Comparison within category - Cover reliability and consistency part - Summarize learnings with expected trends
Distributed Stream Processing - Ronak Chaudhari
- About Stream processing
- Data streams - DBMS vs Stream processing
- Applications
- Monitoring applications - Militia applications - Financial analysis - Tracking applications
- Aurora
- Process incoming streams - It has its own query algebra - System Model - Query Model - Runtime Architecture - QOS criteria - SQuAL - Query algebra - Aurora GUI - Challenges in distribute operation
- Aurora vs Medusa
- Medusa
- Architecture - Addition to Aurora - Lookup and Brain - Failure detection - Transfer of processing - System API - Load management - High availability - Benefits
- References