Emerging Technologies (IoT, Cloud, AI, 5G)
Emerging Technologies covers four current areas: the Internet of Things, cloud computing, artificial intelligence and 5G. The exam tests accurate definitions, layer or service-model identification, and matching a scenario to the right technology.
Core rules and concepts
- IoT has four building blocks: sensors/actuators, connectivity, data processing, and a user interface or application. Examples include smart meters, wearable health bands and smart farming.
- Cloud service models: IaaS supplies virtual machines and storage; PaaS supplies a managed runtime and development platform; SaaS supplies finished software over the internet.
- Cloud deployment: public (shared provider), private (one organization), hybrid (a combination).
- AI is the broad goal of machines performing tasks that need intelligence; machine learning is a subset that learns patterns from data.
- 5G targets enhanced mobile broadband, ultra-reliable low-latency communication (around 1 ms) and massive machine-type communication (many devices per area).
Worked example
A startup wants to deploy a web app but does not want to install or patch servers or the runtime. Which cloud model fits? IaaS would still leave OS and runtime management with the startup; SaaS gives only a finished application with no code deployment control. PaaS provides the managed runtime and deployment platform, so PaaS is correct. If the startup instead rented bare virtual machines and managed the OS itself, IaaS would fit.
Traps that cost marks
- Equating IoT with cloud computing; IoT can process data at the edge without cloud.
- Swapping PaaS and SaaS in scenario questions.
- Defining 5G only as 'faster internet' and missing low latency and device density.
- Calling all AI 'machine learning'; ML is one branch of AI.
- Treating a private cloud as necessarily on-premises; it means dedicated to one organization.