1.1. Cloud Computing Fundamentals

  • 6 Video lectures (48 minutes 20 seconds)

1.1.1. Course Info

Prof. Judy Qiu covers basic information about Unit 1, including lecture schedule and homework submissions. Key cloud computing topics are highlighted. A selection of recommended and required textbooks is given, followed by an overview of the course structure.

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1.1.2. Introduction

Changes in computing technology for the past five decades are discussed. The rise of Big Data is shown in terms of its growth and significance. A prediction is made that the paradigm which has held ‘til now of individual researchers with personal computers will give way to communities of researchers organizing through clouds. A more in-depth look at Unit 1 follows, focusing on the chapters from Distributed and Cloud Computing: From Parallel Processing to the Internet of Things.

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1.1.3. Data Center Model

A look at what truly defines a ‘cloud’. Advantages like scalability and cost-effectiveness have promulgated commercial cloud offerings such as Amazon EC2. Cloud architecture as divided into three layers: Infrastructure as a Service, Platform as a Service, and Software as a Service. AzureBlast is used as an example of how to utilize the cloud setup. Certain misconceptions about clouds are then presented for further discussion.

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1.1.4. Data Intensive Sciences

Some time is spent analyzing the current age of vast data growth, where business, science, and consumer activity has seen an explosion of stored data measured in exobytes. In response to this, the way we conduct scientific research has also undergone an upgrade. However, the average scientist would rather focus on their own research rather than spend time trying to learn different methods of cloud and supercomputing.

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1.1.5. IaaS, PaaS and SaaS

Definitions and examples are given for Infrastructure as a Service, Platform as a Service, and Software as a Service. A chart is shown illustrating how use of clouds trades cost and control for efficiency. Following this is an exploration of the MapReduce program, and an illustration of its concepts through WordCount. Finally, four distinct approaches to MapReduce are compared.

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1.1.6. Challenges

The demands of Big Data calls for advances in areas like distributed computing, systems management, internet technology, and hardware. Clouds have become more prominent in the last few decades, so much so that many people today take advantage of them without even knowing it. Of course, this has also led to increased concerns about security, price, tech support, etc. In spite of this, clouds still have clear advantages over traditional computing models. A quiz is offered at the end asking students to correctly place software in a hierarchy of computing.

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