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.
Este curso faz parte do Programa de cursos integrados Computação em nuvemComputação em Nuvem
Cloud Computing Concepts, Part 1
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Programa de cursos integrados Computação em nuvemComputação em NuvemUniversidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-Champaign
Informações sobre o curso
73,286
73,286Habilidades que você terá
Distributed AlgorithmDistributed ComputingC++Cloud Computing
Programa - O que você aprenderá com este curso
Semana
16 horas para concluir
Week 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 vídeos (total de (Total 155 mín.) min), 8 leituras, 3 testes
16 videos
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23min
Week 1 Introduction1min
1.1. Why Clouds?6min
1.2. What is a Cloud?5min
1.3. Introduction to Clouds: History7min
1.4. Introduction to Clouds: What's New in Today's Clouds7min
1.5. Introduction to Clouds: New Aspects of Clouds8min
1.6. Introduction to Clouds: Economics of Clouds7min
2.1. A cloud IS a distributed system5min
2.2. What is a distributed system?16min
3.1. MapReduce Paradigm14min
3.2. MapReduce Examples10min
3.3. MapReduce Scheduling12min
3.4. MapReduce Fault-Tolerance8min
Interview with Sumeet Singh16min
8 leituras
Orientation Overview10min
Syllabus10min
About the Discussion Forums10min
Instructions for Taking the Prerequisite Quiz10min
Course Learning Community and Social Media10min
Week 1 Overview10min
Homework 1 Instructions10min
Programming Assignment Instructions10min
3 exercícios práticos
Orientation Quiz10min
Prerequisite Quiz50min
Homework 114min
Semana
23 horas para concluir
Week 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 vídeos (total de (Total 122 mín.) min), 2 leituras, 1 teste
14 videos
1.1. Multicast Problem9min
1.2. The Gossip Protocol5min
1.3. Gossip Analysis15min
1.4. Gossip Implementations4min
2.1. What is Group Membership List?8min
2.2. Failure Detectors9min
2.3. Gossip-Style Membership7min
2.4. Which is the best failure detector?4min
2.5. Another Probabilistic Failure Detector9min
2.6. Dissemination and suspicion8min
3.1. Grid Applications6min
3.2. Grid Infrastucture11min
Interview with William Gropp20min
2 leituras
Week 2 Overview10min
Homework 2 Instructions10min
1 exercício prático
Homework 212min
Semana
33 horas para concluir
Week 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 vídeos (total de (Total 105 mín.) min), 2 leituras, 1 teste
10 videos
1. P2P Systems Introduction5min
2. Napster7min
3. Gnutella20min
4. FastTrack and BitTorrent7min
5. Chord22min
6. Failures in Chord14min
7. Pastry6min
8. Kelips10min
Blue Waters Supercomputer9min
2 leituras
Week 3 Overview10min
Homework 3 Instructions10min
1 exercício prático
Homework 328min
Semana
44 horas para concluir
Week 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 vídeos (total de (Total 147 mín.) min), 3 leituras, 1 teste
12 videos
1.1. Why Key-Value/NOSQL?15min
1.2. Cassandra27min
1.3. The Mystery of X-The Cap Theorem19min
1.4. The Consistency Spectrum9min
1.5. HBase10min
2.1. Introduction and Basics10min
2.2. Cristian's Algorithm5min
2.3. NTP4min
2.4. Lamport Timestamps14min
2.5. Vector Clocks12min
Interview with Marcos Aguilera14min
3 leituras
Week 4 Overview10min
Optional: Lamport Timestamps (Ukulele Version)10min
Homework 4 Instructions10min
1 exercício prático
Homework 450min
Semana
58 horas para concluir
Week 5: Classical Distributed Algorithms
Lesson 1: This module covers how to calculate a distributed snapshot, leveraging causality again to circumvent the synchronization problem. Lesson 2: This lecture teaches how to order multicasts in any distributed system. Algorithms for assigning timestamp tags to multicasts using various flavors of ordering – FIFO, Causal, and Total – are covered. The module also covers virtual synchrony, a paradigm that combines reliable multicasts with membership views. Lesson 3: Consensus is one of the most important problems in a distributed system, enabling multiple machines to agree. This module uses Paxos, one of the most popular consensus solutions used in the industry today. Paxos is not perfect because consensus cannot be solved completely – an optional lecture presents the famous FLP proof of impossibility of consensus.
16 vídeos (total de (Total 156 mín.) min), 3 leituras, 3 testes
16 videos
1.1. What is Global Snapshot?7min
1.2. Global Snapshot Algorithm10min
1.3. Consistent Cuts6min
1.4. Safety and Liveness7min
2.1. Multicast Ordering16min
2.2. Implementing Multicast Ordering 19min
2.3. Implementing Multicast Ordering 27min
2.4. Reliable Multicast5min
2.5. Virtual Synchrony11min
3.1. The Consensus Problem12min
3.2. Consensus In Synchronous Systems8min
3.3. Paxos, Simply13min
3.4. The FLP Proof [OPTIONAL]20min
Interview with Tushar Chandra13min
Conclusion to Cloud Computing Concepts, Part 13min
3 leituras
Week 5 Overview10min
Homework 5 Instructions10min
Final Exam Instructions10min
2 exercícios práticos
Homework 530min
Final Exams
20%
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Melhores avaliações
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.
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.
Instrutores
Indranil Gupta
ProfessorDepartment of Computer Science
Comece a trabalhar rumo ao seu mestrado
Este curso é parte da graduação 100% on-line Master in Computer Science da Universidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-Champaign.
Caso seja aceito para o programa completo, seus cursos contarão para sua graduação.
Sobre Universidade de Illinois em Urbana-ChampaignUniversidade de Illinois em 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.
Sobre o Programa de cursos integrados Computação em nuvemComputação em Nuvem
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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