課程信息
4.6
196 個評分
41 個審閱
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為25 小時

建議:5 weeks of study, 5 - 10 hours/week...
可選語言

英語(English)

字幕:英語(English)

您將獲得的技能

Distributed ComputingC++Cloud ComputingNoSQL
專項課程

第 2 門課程(共 6 門)

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為25 小時

建議:5 weeks of study, 5 - 10 hours/week...
可選語言

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 4 小時

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....
Reading
11 個視頻 (總計 122 分鐘), 7 個閱讀材料, 2 個測驗
Video11 個視頻
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23分鐘
Week 1 Introduction1分鐘
1.1. The Election Problem8分鐘
1.2. Ring Leader Election14分鐘
1.3. Election in Chubby and ZooKeeper9分鐘
1.4. Bully Algorithm9分鐘
2.1. Introduction and Basics12分鐘
2.2. Distributed Mutual Exclusion10分鐘
2.3. Ricart-Agrawala's Algorithm11分鐘
2.4. Maekawa's Algorithm and Wrap-Up16分鐘
Reading7 個閱讀材料
Orientation Overview10分鐘
Syllabus10分鐘
About the Discussion Forums10分鐘
Course Learning Community and Social Media10分鐘
Week 1 Overview10分鐘
Homework 1 Instructions10分鐘
Programming Assignment Instructions10分鐘
Quiz2 個練習
Orientation Quiz10分鐘
Homework 120分鐘
2
完成時間(小時)
完成時間為 2 小時

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. ...
Reading
8 個視頻 (總計 95 分鐘), 2 個閱讀材料, 1 個測驗
Video8 個視頻
1.1. RPCs17分鐘
1.2. Transactions13分鐘
1.3. Serial Equivalence12分鐘
1.4. Pessimistic Concurrency13分鐘
1.5. Optimistic Concurrency Control9分鐘
2.1. Replication14分鐘
2.2. Two-Phase Commit11分鐘
Reading2 個閱讀材料
Week 2 Overview10分鐘
Homework 2 Instructions10分鐘
Quiz1 個練習
Homework 230分鐘
3
完成時間(小時)
完成時間為 3 小時

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....
Reading
9 個視頻 (總計 110 分鐘), 2 個閱讀材料, 1 個測驗
Video9 個視頻
Stream Processing in Storm15分鐘
Distributed Graph Processing16分鐘
Structure of Networks21分鐘
4.1. Single-processor Scheduling11分鐘
4.2. Hadoop Scheduling11分鐘
4.3. Dominant-Resource Fair Scheduling8分鐘
Storm Demo 9分鐘
Apache Spark by Faria Kalim12分鐘
Reading2 個閱讀材料
Week 3 Overview10分鐘
Homework 3 Instructions10分鐘
Quiz1 個練習
Homework 330分鐘
4
完成時間(小時)
完成時間為 3 小時

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....
Reading
6 個視頻 (總計 109 分鐘), 2 個閱讀材料, 1 個測驗
Video6 個視頻
1.1. File System Abstraction23分鐘
1.2. NFS and AFS14分鐘
Distributed Shared Memory17分鐘
Sensor and Their Networks30分鐘
Interview with Brighten Godfrey23分鐘
Reading2 個閱讀材料
Week 4 Overview10分鐘
Homework 4 Instructions10分鐘
Quiz1 個練習
Homework 420分鐘
4.6
41 個審閱Chevron Right

熱門審閱

創建者 MRJul 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.

創建者 AHJan 1st 2018

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

講師

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Indranil Gupta

Professor
Department of Computer Science
Graduation Cap

立即開始攻讀碩士學位

此 課程 隸屬於 伊利诺伊大学香槟分校 提供的 100% 在線 Master in Computer Science。如果您被錄取參加全部課程,您的課程將計入您的學位學習進程。

關於 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. ...

關於 云计算 專項課程

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....
云计算

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