1. Distributed Systems (15-440) Mohammad Hammoud December 4 th, 2013

2. Course Objectives The course aims at providing an in- depth and hands-on understanding on Principles on which distributed systems are based Principles on which distributed systems are optimized Distributed system programming models and analytics engines How modern distributed systems meet the demands of contemporary distributed applications

3. List of Topics.1. Architectures and Communications.2. Naming.3. Synchronization.4. Consistency and Replication.5. Fault Tolerance.6. Programming Models.7. Distributed File Systems.8. Virtualization Considered: a reasonably critical and comprehensive understanding. Thoughtful: Fluent, flexible and efficient understanding. Masterful: a powerful and illuminating understanding.

4. Course Content  Course Overview and Introduction (2 Lectures): – Why distributed systems? – Defining distributed systems – Course overview and intended learning outcomes – Trends in distributed systems High performance platforms Mobile and ubiquities computing Cloud computing Etc., – Challenges in designing distributed systems Heterogeneity, openness, security, scalability, reliability, concurrency, transparency and quality of service

5. Course Content  Architectural Models (1 Lecture): – Client-server, peer-to-peer, tiered and layered architectures  Networking (1 Lecture): – Types of networks – Networking principles: Packet transmission Network Layers (Physical, data-link, network and transport layers) Congestion control

6. Course Content  Communication Paradigms (1 Lecture): – Socket communication TCP and UDP sockets – Remote invocation RPC and RMI – Indirect communication Message-queuing, publish-subscribe, and group communication systems

7. Course Content  Naming (2 Lectures): – Flat naming Broadcasting, forwarding pointers, home-based naming, and distributed hash tables – Structured naming Hierarchical name spaces, name resolution, linking and mounting – Attribute-based naming LDAP and RDF

8. Course Content  Synchronization (3 Lectures): – Time synchronization Physical clocks (UTC, Cristian & Berkeley Algorithms and Network Time Protocol) Logical clocks (Lamport and vector clocks) – Distributed Mutual Exclusion Permission-based Token-based – Election Algorithms Bully and Ring algorithms

9. Course Content  Consistency and Replication (3 Lectures): – Data-Centric Consistency Models: Continuous, Sequential and Causal Models – Client-Centric Consistency Models: Eventual consistency and client consistency guarantees – Replica Management: Server and content replication and placement strategies – Consistency Protocols: Primary-based, replicated-write and cache coherence protocols

10. Course Content  Distributed Programming Models (4 Lectures): – Classical programming models Shared-memory and message-passing models – MPI Library Point-to-point and group communication routines – Hadoop MapReduce, Google’s Pregel and CMU’s GraphLab The parallelism models The programming models The architectural models The computational models Task/Vertex/Job scheduling Distributed application suitability

11. Course Content  Fault-Tolerance (3 Lectures) – Failure models Crash, omission, timing, response and byzantine models – Process resilience and agreement protocols Lamport’s agreement protocol – Reliable communication Request-reply reliable communication ( Request-reply call semantics) Group reliable communication ( Virtual synchrony and atomic multicasting) – Recovery ( Checkpointing and message-logging)

12. Course Content  Distributed File Systems (2 Lectures): – DFS Aspects: Architectures ( Client-server, cluster-based, and symmetric architectures) Processes (Stateless vs. state-full processes) Communication (RPC2) Naming (Constructing global name spaces) Synchronization (Semantics of file sharing) Consistency and replication (Client-side caching, server- side replication and versioning) Fault-tolerance (Quorum-based mechanisms)

13. Course Content  Virtualization (1 Lecture): – Why Virtualization in distributed systems? – Virtualization types Full virtualization vs. para-virtualization – Virtual machine types Process VMs vs. system VMs