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.
This course builds on the material covered in the Cloud Computing Concepts, Part 1 course.
教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 4 小时
Week 1: Course Orientation and Classical Distributed Algorithms Continued
Lesson 1: To coordinate machines in a distributed system, this module first looks at classical algorithms for electing a leader, including the Ring algorithm and Bully algorithm. We also cover how Google’s Chubby and Apache Zookeeper solve leader election. Lesson 2: This module covers solutions to the problem of mutual exclusion, which is important for correctness in distributed systems with shared resources. We cover classical algorithms, including Ricart-Agrawala’s algorithm and Maekawa’s algorithm. We also cover Google’s Chubby support for mutual exclusion.
11 个视频 （总计 122 分钟）, 7 个阅读材料, 2 个测验
11 个视频
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23分钟
Week 1 Introduction1分钟
1.1. The Election Problem8分钟
1.2. Ring Leader Election14分钟
1.3. Election in Chubby and ZooKeeper9分钟
1.4. Bully Algorithm9分钟
2.1. Introduction and Basics12分钟
2.2. Distributed Mutual Exclusion10分钟
2.3. Ricart-Agrawala's Algorithm11分钟
2.4. Maekawa's Algorithm and Wrap-Up16分钟
7 个阅读材料
Orientation Overview10分钟
Syllabus10分钟
About the Discussion Forums10分钟
Course Learning Community and Social Media10分钟
Week 1 Overview10分钟
Homework 1 Instructions10分钟
Programming Assignment Instructions10分钟
2 个练习
Orientation Quiz10分钟
Homework 120分钟
周
2完成时间为 2 小时
Week 2: Concurrency and Replication Control
Lesson 1: Transactions are an important component of many cloud systems today. This module presents building blocks to ensure transactions work as intended, from Remote Procedure Calls (RPCs), to serial equivalence for transactions, to optimistic and pessimistic approaches to concurrency control, to deadlock avoidance/prevention. Lesson 2: This module covers how replication – maintaining copies of the same data at different locations – is used to provide many nines of availability in distributed systems, as well as different techniques for replication and for ensuring transactions commit correctly in spite of replication.
8 个视频 （总计 95 分钟）, 2 个阅读材料, 1 个测验
8 个视频
1.1. RPCs17分钟
1.2. Transactions13分钟
1.3. Serial Equivalence12分钟
1.4. Pessimistic Concurrency13分钟
1.5. Optimistic Concurrency Control9分钟
2.1. Replication14分钟
2.2. Two-Phase Commit11分钟
2 个阅读材料
Week 2 Overview10分钟
Homework 2 Instructions10分钟
1 个练习
Homework 230分钟
周
3完成时间为 3 小时
Week 3: Emerging Paradigms
Lesson 1: We study the emerging area of stream processing, touching on key design aspects of Apache Storm. Lesson 2: We study how enormous graphs can be processed in clouds. Lesson 3: We study various types of networks/graphs that are both natural and artificial, and their surprising commonalities. Lesson 4: This module presents classical scheduling algorithms that have been used in operating systems since the inception of computers. We then cover two popular scheduling algorithms for Hadoop.
9 个视频 （总计 110 分钟）, 2 个阅读材料, 1 个测验
9 个视频
Stream Processing in Storm15分钟
Distributed Graph Processing16分钟
Structure of Networks21分钟
4.1. Single-processor Scheduling11分钟
4.2. Hadoop Scheduling11分钟
4.3. Dominant-Resource Fair Scheduling8分钟
Storm Demo 9分钟
Apache Spark by Faria Kalim12分钟
2 个阅读材料
Week 3 Overview10分钟
Homework 3 Instructions10分钟
1 个练习
Homework 330分钟
周
4完成时间为 3 小时
Week 4: Classical Systems
Lesson 1: When files and directories are stored/accessed over the network, it is called a distributed file system. This module covers the working of distributed file systems like NFS and AFS. Lesson 2: This module covers Distributed Shared Memory systems, their techniques, and pros/cons. Lesson 3: This module looks at the area of sensor networks, starting from what’s inside a sensor mote and how networks of them work.
6 个视频 （总计 109 分钟）, 2 个阅读材料, 1 个测验
6 个视频
1.1. File System Abstraction23分钟
1.2. NFS and AFS14分钟
Distributed Shared Memory17分钟
Sensor and Their Networks30分钟
Interview with Brighten Godfrey23分钟
2 个阅读材料
Week 4 Overview10分钟
Homework 4 Instructions10分钟
1 个练习
Homework 420分钟
周
5完成时间为 7 小时
Week 5: Real-Life Behaviors
Lesson 1: This module is a primer on basic security concepts, not just applied to distributed systems, but also more generally. We study various policies and mechanisms, including encryption, authentication, and authorization. Lesson 2: This module presents case studies of real datacenter outages, and attempts to draw lessons on how to prevent them and how to better prepare for them.
11 个视频 （总计 102 分钟）, 3 个阅读材料, 3 个测验
11 个视频
1.1. Basic Security Concepts9分钟
1.2. Basic Cryptography Concepts8分钟
1.3. Implementing Mechanism using Cryptography15分钟
2.1. What Causes Disasters?6分钟
2.2. AWS Outage14分钟
2.3. Facebook Outage5分钟
2.4. The Planet Outage5分钟
2.5. Wrap-Up7分钟
Interview with Paul Kwiat24分钟
Conclusion to Cloud Computing Concepts, Part 23分钟
3 个阅读材料
Week 5 Overview10分钟
Homework 5 Instructions10分钟
Final Exam Instructions10分钟
2 个练习
Homework 520分钟
Final Exam
4.6
47 个审阅热门审阅
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.
Very nice and informative course, and the programming assignment in the end of the course is so helpful to understand and apply the theoretical concepts that was introduced during the course
讲师
Indranil Gupta
ProfessorDepartment of Computer Science
领先获取学位
此 课程 隶属于 伊利诺伊大学香槟分校 提供的 100% 在线 Master in Computer Science。立即开始学习开放课程或专项课程，观看 iMBA 教师的课程并完成自主学习作业。
完成每门课程后，您将获得一个证书，您可以添加到 LinkedIn 和简历中。
如果申请并被录取参加全部课程，您的课程将计入您的学位学习进程。
关于 伊利诺伊大学香槟分校
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.
关于 云计算 专项课程
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.
常见问题
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
退款政策是如何规定的？
有助学金吗？
还有其他问题吗？请访问 学生帮助中心。
