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. Ins...

Full description

Saved in:
Bibliographic Details
Main Authors: Barve, Yogesh D., Patil, Prithviraj, Gokhale, Aniruddha
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Cloud
Cloud computing
Computer networks
Computer programs
Computer simulation
Distributed algorithms
Distributed Systems
Education
Feature model
Java
Learning
Learning System
Mathematical models
Peer-to-peer computing
Software
Software algorithms
Software Product Lines
Teaching
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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 system algorithms is needed to complement existing teaching modalities. Such an environment must be flexible to support learning of a variety of algorithms. Moreover, since many of these algorithms share several common traits with each other while differing only in some aspects, the environment should support extensibility and reuse. 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 (SPLs) and model-driven engineering and adopt the cloud platform to design an immersive learning environment called the Playground of Algorithms for Distributed Systems (PADS). The research contributions in PADS include the underlying feature model, the design of a domainspecific modeling language that supports the feature model, and the generative capabilities that maximally automate the synthesis of experiments on cloud platforms. A prototype implementation of PADS is described to showcase a distributed systems algorithm illustrating a peer to peer file transfer algorithm based on BitTorrent, which shows the benefits of rapid deployment of the distributed systems algorithm.
ISSN:0730-3157
DOI:10.1109/COMPSAC.2016.26