How do you compare computing models for computer engineering?

2 Cloud computing

Cloud computing is a computing model that provides on-demand access to shared resources and services over the internet, such as storage, processing, networking, software, and platforms. Cloud computing enables users to access and use computing resources without having to own, manage, or maintain them, which reduces the cost, complexity, and risk of IT infrastructure. Cloud computing also offers scalability, elasticity, and availability, which means that users can adjust the amount and type of resources they need according to their changing demands and preferences. Cloud computing can be classified into different service models, such as infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS), and different deployment models, such as public, private, hybrid, and community clouds.

3 Edge computing

Edge computing is a computing model that moves the computation and data processing closer to the source of the data, such as sensors, devices, or users, rather than relying on centralized servers or clouds. Edge computing aims to reduce the latency, bandwidth, and energy consumption of data transmission and processing, which improves the performance, efficiency, and security of the system. Edge computing also enables real-time and context-aware processing of data, which supports applications that require low latency, high reliability, and high privacy, such as autonomous vehicles, smart cities, and augmented reality. Edge computing can be implemented in different ways, such as using edge devices, edge nodes, edge servers, or edge clouds.

4 Quantum computing

Quantum computing is a computing model that uses the principles of quantum mechanics to perform computation, such as superposition, entanglement, and interference. Quantum computing uses quantum bits or qubits, which can represent both 0 and 1 at the same time, rather than binary bits, which can only represent either 0 or 1. Quantum computing can potentially solve problems that are intractable or impractical for classical computers, such as optimization, encryption, simulation, and machine learning. Quantum computing is still in its early stages of development and faces many challenges, such as creating and maintaining qubits, controlling and measuring quantum states, and scaling and integrating quantum systems.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?