CS3551 Distributed Computing Syllabus:
CS3551 Distributed Computing Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
To introduce the computation and communication models of distributed systems
To illustrate the issues of synchronization and collection of information in distributed systems
To describe distributed mutual exclusion and distributed deadlock detection techniques
To elucidate agreement protocols and fault tolerance mechanisms in distributed systems
To explain the cloud computing models and the underlying concepts
UNIT I INTRODUCTION
Introduction: Definition-Relation to Computer System Components – Motivation – Message -Passing Systems versus Shared Memory Systems – Primitives for Distributed Communication – Synchronous versus Asynchronous Executions – Design Issues and Challenges; A Model of Distributed Computations: A Distributed Program – A Model of Distributed Executions – Models of Communication Networks – Global State of a Distributed System.
UNIT II LOGICAL TIME AND GLOBAL STATE
Logical Time: Physical Clock Synchronization: NTP – A Framework for a System of Logical Clocks – Scalar Time – Vector Time; Message Ordering and Group Communication: Message Ordering Paradigms – Asynchronous Execution with Synchronous Communication – Synchronous Program Order on Asynchronous System – Group Communication – Causal Order – Total Order; Global State and Snapshot Recording Algorithms: Introduction – System Model and Definitions – Snapshot Algorithms for FIFO Channels.
UNIT III DISTRIBUTED MUTEX AND DEADLOCK
Distributed Mutual exclusion Algorithms: Introduction – Preliminaries – Lamport’s algorithm – Ricart Agrawala’s Algorithm –– Token-Based Algorithms – Suzuki-Kasami’s Broadcast Algorithm; Deadlock Detection in Distributed Systems: Introduction – System Model – Preliminaries – Models of Deadlocks – Chandy-Misra-Haas Algorithm for the AND model and OR Model.
UNIT IV CONSENSUS AND RECOVERY
Consensus and Agreement Algorithms: Problem Definition – Overview of Results – Agreement in a Failure-Free System(Synchronous and Asynchronous) – Agreement in Synchronous Systems with Failures; Checkpointing and Rollback Recovery: Introduction – Background and Definitions – Issues in Failure Recovery – Checkpoint-based Recovery – Coordinated Checkpointing Algorithm – – Algorithm for Asynchronous Checkpointing and Recovery
UNIT V CLOUD COMPUTING
Definition of Cloud Computing – Characteristics of Cloud – Cloud Deployment Models – Cloud Service Models – Driving Factors and Challenges of Cloud – Virtualization – Load Balancing – Scalability and Elasticity – Replication – Monitoring – Cloud Services and Platforms: Compute Services – Storage Services – Application Services
COURSE OUTCOMES:
Upon the completion of this course, the student will be able to
CO1: Explain the foundations of distributed systems
CO2: Solve synchronization and state consistency problems
CO3 Use resource sharing techniques in distributed systems
CO4: Apply working model of consensus and reliability of distributed systems
CO5: Explain the fundamentals of cloud computing
TOTAL:45 PERIODS
TEXT BOOKS
1. Kshemkalyani Ajay D, Mukesh Singhal, “Distributed Computing: Principles, Algorithms and Systems”, Cambridge Press, 2011.
2. Mukesh Singhal, Niranjan G Shivaratri, “Advanced Concepts in Operating systems”, McGraw Hill Publishers, 1994.
REFERENCES
1. George Coulouris, Jean Dollimore, Time Kindberg, “Distributed Systems Concepts and Design”, Fifth Edition, Pearson Education, 2012.
2. Pradeep L Sinha, “Distributed Operating Systems: Concepts and Design”, Prentice Hall of India, 2007.
3. Tanenbaum A S, Van Steen M, “Distributed Systems: Principles and Paradigms”, Pearson Education, 2007.
4. Liu M L, “Distributed Computing: Principles and Applications”, Pearson Education, 2004.
5. Nancy A Lynch, “Distributed Algorithms”, Morgan Kaufman Publishers, 2003.
6. Arshdeep Bagga, Vijay Madisetti, “ Cloud Computing: A Hands-On Approach”, Universities Press, 2014.