PADS: Design and Implementation of a Cloud-Based, Immersive Learning Environment for Distributed Systems Algorithms

As distributed systems become more complex, understanding the underlying algorithms that make these systems work becomes even harder. Traditional learning modalities based on didactic teaching and theoretical proofs alone are no longer sufficient for a holistic understanding of these algorithms. Instead, an environment that promotes an immersive, hands-on learning of distributed systems algorithms is needed to complement existing teaching modalities. Such an environment must be flexible to support the learning of a variety of algorithms. The environment should also support extensibility and reuse since many of these algorithms share several common traits with each other while differing only in some aspects. Finally, it must also allow students to experiment with large-scale deployments in a variety of operating environments. To address these concerns, we use the principles of software product lines and model-driven engineering, and adopt the cloud platform to design an immersive learning environment called the Playground of Algorithms for Distributed Systems (PADS). A prototype implementation of PADS is described to showcase use cases involving BitTorrent Peer-to-Peer file sharing, ZooKeeper-based coordination, and Paxos-based consensus, which show the benefits of rapid deployment of the distributed systems algorithms. Results from a preliminary user study are also presented.