Cloud Computing has become a dominant paradigm for cost-effective, scalable, and well-managed computing, playing a crucial role in enabling fields such as the Internet of Things (IoT) and Machine Learning. Major companies like Amazon, Google, Microsoft, and Facebook have heavily invested in Cloud Computing to meet the rising demand for cloud services. Users benefit from the flexibility and efficiency of shared, power-efficient cloud data centers, allowing them to meet dynamic computing needs without incurring unnecessary costs. This course will cover foundational Cloud Computing concepts such as the basics of Cloud Computing, service provisioning and deployment models, networking, and security in the cloud as well as virtualization and containerization technologies used in Cloud Computing. Serverless computing, big data analytics, and machine learning on the cloud will also be discussed. We will further survey the advanced aspects of Cloud Computing by examining recent research published at top conferences, executing Cloud Computing tasks on a state of the art cloud computing service (such as Google's Google Cloud Platform (GCP) and Amazon's Amazon Web Services (AWS)), and implementing a change or feature in a state of the art Cloud Computing framework. Suggested prerequisites: CS 270 and/or CS 371; This class is appropriate for graduate students with previous background in operating system and networking.
This course is a special topics course. The topic and syllabus will change each time the course is offered, reflecting the interests of the instructor. Typically the course will survey new research in the topic area but may also look back at canonical and ground breaking work from the past. Example course topics might include things such as web operating systems, global file systems, distributed object-based systems, fault tolerance/distributed check pointing, high-speed networking, network security, active networking, group communication models, compilers for parallel/distributed computing, recent programming languages, and data mining.
This course is a special topics course. The topic and syllabus will change each time the course is offered, reflecting the interests of the instructor. Typically the course will survey new research in the topic area but may also look back at canonical and ground breaking work from the past. Example course topics might include things such as web operating systems, global file systems, distributed object-based systems, fault tolerance/distributed check pointing, high-speed networking, network security, active networking, group communication models, compilers for parallel/distributed computing, recent programming languages, and data mining.
