Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing.
Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more!
Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises. In the programming assignments, implement some of these concepts in template code (programs) provided in the C++ programming language. Prior experience with C++ is required.
The course also features interviews with leading researchers and managers, from both industry and academia.
Ce cours fait partie de la Spécialisation Cloud Computing
Cloud Computing Concepts, Part 1
proposé par
À propos de ce cours
4.5
605 notes
Compétences que vous acquerrez
Distributed AlgorithmDistributed ComputingC++Cloud Computing
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Week 1: Orientation, Introduction to Clouds, MapReduce
This course is oriented towards learners with similar backgrounds as juniors and seniors in a CS undergraduate curriculum. Since learners come from various backgrounds, it is critical you view this lecture AND pass the prerequisite test. This will ensure you have many of the assumed prerequisite pieces of knowledge required to enjoy this course.
16 vidéos (Total 155 min), 8 lectures, 3 quiz
16 vidéos
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23 min
Week 1 Introduction1 min
1.1. Why Clouds?6 min
1.2. What is a Cloud?5 min
1.3. Introduction to Clouds: History7 min
1.4. Introduction to Clouds: What's New in Today's Clouds7 min
1.5. Introduction to Clouds: New Aspects of Clouds8 min
1.6. Introduction to Clouds: Economics of Clouds7 min
2.1. A cloud IS a distributed system5 min
2.2. What is a distributed system?16 min
3.1. MapReduce Paradigm14 min
3.2. MapReduce Examples10 min
3.3. MapReduce Scheduling12 min
3.4. MapReduce Fault-Tolerance8 min
Interview with Sumeet Singh16 min
8 lectures
Orientation Overview10 min
Syllabus10 min
About the Discussion Forums10 min
Instructions for Taking the Prerequisite Quiz10 min
Course Learning Community and Social Media10 min
Week 1 Overview10 min
Homework 1 Instructions10 min
Programming Assignment Instructions10 min
3 exercices pour s'entraîner
Orientation Quiz10 min
Prerequisite Quiz50 min
Homework 114 min
Semaine
2Week 2: Gossip, Membership, and Grids
Lesson 1: This module teaches how the multicast problem is solved by using epidemic/gossip protocols. It also teaches analysis of such protocols. Lesson 2: This module covers the design of failure detectors, a key component in any distributed system. Membership protocols, which use failure detectors as components, are also covered. Lesson 3: This module covers Grid computing, an important precursor to cloud computing.
14 vidéos (Total 122 min), 2 lectures, 1 quiz
14 vidéos
Week 2 Introduction1 min
1.1. Multicast Problem9 min
1.2. The Gossip Protocol5 min
1.3. Gossip Analysis15 min
1.4. Gossip Implementations4 min
2.1. What is Group Membership List?8 min
2.2. Failure Detectors9 min
2.3. Gossip-Style Membership7 min
2.4. Which is the best failure detector?4 min
2.5. Another Probabilistic Failure Detector9 min
2.6. Dissemination and suspicion8 min
3.1. Grid Applications6 min
3.2. Grid Infrastucture11 min
Interview with William Gropp20 min
2 lectures
Week 2 Overview10 min
Homework 2 Instructions10 min
1 exercice pour s'entraîner
Homework 212 min
Semaine
3Week 3: P2P Systems
P2P systems: This module teaches the detailed design of two classes of peer to peer systems: (a) popular ones including Napster, Gnutella, FastTrack, and BitTorrent; and (b) efficient ones including distributed hash tables (Chord, Pastry, and Kelips). Besides focusing on design, the module also analyzes these systems in detail.
10 vidéos (Total 105 min), 2 lectures, 1 quiz
10 vidéos
Week 3 Introduction1 min
1. P2P Systems Introduction5 min
2. Napster7 min
3. Gnutella20 min
4. FastTrack and BitTorrent7 min
5. Chord22 min
6. Failures in Chord14 min
7. Pastry6 min
8. Kelips10 min
Blue Waters Supercomputer9 min
2 lectures
Week 3 Overview10 min
Homework 3 Instructions10 min
1 exercice pour s'entraîner
Homework 328 min
Semaine
4Week 4: Key-Value Stores, Time, and Ordering
Lesson 1: This module motivates and teaches the design of key-value/NoSQL storage/database systems. We cover the design of two major industry systems: Apache Cassandra and HBase. We also cover the famous CAP theorem. Lesson 2: Distributed systems are asynchronous, which makes clocks at different machines hard to synchronize. This module first covers various clock synchronization algorithms, and then covers ways of tagging events with causal timestamps that avoid synchronizing clocks. These classical algorithms were invented decades ago, yet are used widely in today’s cloud systems.
12 vidéos (Total 147 min), 3 lectures, 1 quiz
12 vidéos
Week 4 Introduction2 min
1.1. Why Key-Value/NOSQL?15 min
1.2. Cassandra27 min
1.3. The Mystery of X-The Cap Theorem19 min
1.4. The Consistency Spectrum9 min
1.5. HBase10 min
2.1. Introduction and Basics10 min
2.2. Cristian's Algorithm5 min
2.3. NTP4 min
2.4. Lamport Timestamps14 min
2.5. Vector Clocks12 min
Interview with Marcos Aguilera14 min
3 lectures
Week 4 Overview10 min
Optional: Lamport Timestamps (Ukulele Version)10 min
Homework 4 Instructions10 min
1 exercice pour s'entraîner
Homework 450 min
4.5
155 avisMeilleurs avis
par MR•Jul 16th 2017
Great course, I would recommend to everyone who wants to understand the basics of cloud computing. The course material is excellent, the instructor Indy is phenomenal and the exams are marvelous.
par DP•Oct 7th 2016
This instructor is fantastic. He is exceptionally thorough and his delivery is very good as well. This is a course definitely worth taking if you are interested in learning more about the cloud.
Enseignant
Indranil Gupta
ProfessorDepartment of Computer Science
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master in Computer Science de University of Illinois at Urbana-Champaign.
Si vous êtes admis au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
À propos de University of Illinois at Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
À propos de la Spécialisation Cloud Computing
The Cloud Computing Specialization takes you on a tour through cloud computing systems. We start in in the middle layer with Cloud Computing Concepts covering core distributed systems concepts used inside clouds, move to the upper layer of Cloud Applications and finally to the lower layer of Cloud Networking. We conclude with a project that allows you to apply the skills you've learned throughout the courses.
The first four courses in this Specialization form the lecture component of courses in our online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.
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