DistOS 2014W Lecture 23

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?

- 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

• References