Large-Scale Distributed System Design

Large-Scale Distributed System Design
Principles and concepts of designing and building distributed systems. Introduction to architectures for distributed computation. Reliability, availability, and scalability of large applications. Cloud computing and APIs.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesC S 340 & C S 360
 ProgramsContaining C S 462
Course Outcomes

Computational Practice

  • Students can implement programming projects that display knowledge of a variety of distributed system architectural styles. Some of these assignments represent significant programming projects with wide leeway in design and implementation choices.
  • Students will analyze problems, determine solutions within an assigned architectural style, and successfully implement those solutions.
  • Students will design and implement projects both individually and as part of a team.
  • Students will use cloud-based systems to run and implement assignments
  • Students will manage a cloud-based Web server and properly configure it.

Computational Theory

Students will understand the proper use of distributed and decentralized architectures and algorithms including

  • RESTful APIs
  • Hierarchical vs heterarchical system architectures
  • MapReduce
  • Distributed Hash Tables
  • Event-driven system
  • Peer-to-peer architectures including Paxos, gossip protocols, and blockchain

Students will understand theoretical concepts and limitations of distributed systems including

  • network practicalities such as latency, bandwidth, topology, cost, heterogeneity, security
  • CAP theorem
  • distributed transactions
  • serialization
  • identity and naming
  • cryptography
  • simultaneity

Critical Thinking and Communication

Students will interact with peers in meaningful discussion, lead discussions in peer groups, prepare written reports, and make oral presentations.

Ethics and Computing

Students will be presented with societal outcomes of technological choices in distributed and decentralized systems, analyze those outcomes, explore possible alternatives from different choices, and present their findings in small groups.