DistOS 2014W Lecture 23: Difference between revisions
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- Summarize learnings with expected trends | - Summarize learnings with expected trends | ||
===Ronak Chaudhari=== | ===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 |
Revision as of 15:18, 3 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 do not need to worry about installation of the underlying network
- Theme, Argument Outline
- Look at various control frameworks proposed
- 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?
- Define 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% 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 shoudn'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 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 mgmt, Consistency, Access control, Recover metadata in case of crash, Talk to each other 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 with in ctageory - 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