
Explore software defined networking (sdn) architecture and its separation of control and data planes, with a centralized controller and layered infrastructure, to improve network control and management.
Explore cloud storage models and cloud computing for IoT, and learn how web application messaging protocol (WAMP) enables publish-subscribe and remote procedure calls with brokers, publishers, subscribers, and dealers.
Explore the Xively cloud for IoT as a scalable platform as a service with RESTful APIs and Django-based Python web apps.
Explore AWS IoT services, including EC2 for scalable compute, auto scaling, S3 for storage, DynamoDB, Kinesis for real-time streaming, SQS for messaging, and EMR for big data analytics.
In this course, learners will be going to study various cloud platforms required for the Internet of Things (IoT) applications. To study this course, learners must be aware of the concept of the Internet of Things (IoT). In the beginning, learners will be going to learn about Software Defined Networking (SDN), SDN Architecture, How SDN Works, Benefits of SDN, Challenges in SDN, various Use Cases of SDN. After that, learners will be going to study various Cloud Storage Models and different Communication API. After this, learners will be going to study the WAMP: AutoBahn for Internet of Things (IoT) and the Xively Cloud for Internet of Things (IoT). Then learners will be going to study the Python Web Application Framework: Django and its Architecture. Later on, learners will be going to study various Amazon Web Services for Internet of Things (IoT) like EC2, Auto Scaling, S3, RDS, DynamoDB, Kinesis, SQS, EMR, etc. Then learners will also be going to study the Sky Net IoT Messaging Platform. And at the end of this course, learners will be going to study the Google Remote Procedure Call (gRPC) and Simple Object Access Protocol (SOAP). After successful completion of this course, learners will be able to understand various cloud platforms that can be used to implement cloud-based IoT applications.