Lecture-09: Fog Computing, Edge Computing, Quantum Computing and Grid Computing (CC)

 Different Cloud Computing

1. Fog Computing

Definition:
Fog computing is an extension of cloud computing that brings computation, storage, and networking services closer to the data source — between the cloud and edge devices.
It reduces latency and bandwidth usage by processing data locally before sending it to the cloud.

Example:
In a smart traffic system, sensors on the road collect vehicle speed and congestion data.
Instead of sending all this data to a distant cloud server, a fog node (like a local gateway or router) processes it nearby to control traffic lights in real-time.
Only summarized data is sent to the cloud for analysis later.

2. Edge Computing

Definition:
Edge computing means performing data processing directly on the devices (or near the source) where data is generated — such as sensors, IoT devices, or smartphones — instead of relying on centralized cloud servers.
It offers ultra-low latency and faster response.

Example:
A self-driving car uses sensors and cameras to detect objects and make split-second driving decisions.
It cannot wait for cloud servers to respond — so the data is processed onboard (at the edge) for immediate action.

 3. Quantum Computing

Definition:
Quantum computing uses the principles of quantum mechanics (like superposition and entanglement) to process information using qubits instead of bits.
It can perform complex calculations much faster than classical computers for certain types of problems.

Example:
Quantum computers (like IBM’s Quantum System One) can simulate molecular interactions to help design new drugs — something classical computers would take years to calculate.

 

4. Grid Computing

Definition:
Grid computing combines the processing power of multiple computers across different locations to work on a common task.
These computers are connected through a network and share resources (CPU, memory, storage) as if they were a single supercomputer.

Example:
The SETI@home project uses idle computers worldwide to analyze radio signals from space, searching for extraterrestrial life.
Each computer processes a small portion of the data and sends back results to the central server.

 

 Summary Table:

Type	Definition	Example	Key Benefit
Fog Computing	Extends cloud closer to devices	Smart traffic control	Reduces latency
Edge Computing	Processing done at or near data source	Self-driving car	Real-time response
Quantum Computing	Uses qubits & quantum physics	Drug discovery	Solves complex problems
Grid Computing	Uses many distributed computers together	SETI@home project	Massive computing power

 

Main Differences

Feature	Edge Computing	Fog Computing	Grid Computing	Quantum Computing
Definition	Processing data directly at or near the data source (e.g., IoT devices)	Acts as a bridge between edge and cloud — processing happens in local nodes or gateways	Uses distributed computers connected over a network to work together on a shared problem	Uses quantum mechanics principles and qubits for computation
Main Goal	Reduce latency and make real-time decisions	Extend cloud services closer to users for faster data handling	Share computational resources for large-scale processing	Solve complex, non-linear problems much faster than classical computers
Where Processing Happens	On the device itself (or nearby sensor/controller)	In local fog nodes (routers, gateways, micro data centers)	On multiple connected computers distributed across locations	Inside a quantum processor (using qubits and quantum circuits)
Connection with Cloud	May work independently of cloud	Works in collaboration with cloud computing	Works with a central coordinator, not cloud-dependent	Not cloud-based; uses quantum hardware
Latency	Lowest — processing at the edge	Low — processing near edge but not on it	High — depends on network and number of nodes	Varies — depends on quantum algorithm and setup
Use Case Example	Self-driving cars, smart cameras	Smart cities, industrial IoT systems	Scientific simulations, climate modeling	Drug discovery, cryptography, optimization problems
Scalability	Limited (depends on device hardware)	Moderate (depends on number of fog nodes)	High (can use thousands of computers)	Currently low, as quantum tech is emerging
Data Transmission	Minimal — processed locally	Moderate — some data sent to cloud	Large — shared across many systems	Not network-based; relies on quantum circuits
Technology Type	Distributed computing (local)	Distributed computing (intermediate layer)	Parallel/distributed computing	Advanced computation model (quantum physics)

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🧩 In Simple Terms:

• Edge Computing → Data is processed right where it’s created.
• Fog Computing → Data is processed close to the source, but through an intermediate fog layer before reaching the cloud.
• Grid Computing → Many computers work together over a network to solve one big problem.
• Quantum Computing → Uses quantum physics to process information in ways classical computers cannot.