Edge Computing vs Fog Computing – Geeky Gadgets

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edge computing and fog computing. Edge computing, as the name suggests, brings computation closer to the data source, reducing latency and improving efficiency. It involves deploying computational resources, such as servers, at the edge of the network, closer to the devices generating the data. This allows for real-time processing and analysis of data locally, minimizing the need for data transmission to the cloud. Fog computing, on the other hand, sits between the edge and the cloud, offering a hybrid approach.

**I. Edge Computing:**

* **Concept:** Edge computing brings processing power closer to data sources, reducing latency and improving real-time responsiveness. * **Mechanism:** Data is processed directly on edge devices, minimizing data transmission to the cloud.

This layer, often referred to as the “fog,” is responsible for processing data locally, but also for caching and distributing it to other devices. **Key Features of Fog Computing:**

* **Decentralized Processing:** Data is processed closer to the source, reducing latency and improving response times. * **Local Data Caching:** Fog nodes can store and cache frequently accessed data, reducing the need for constant communication with the cloud. * **Dynamic Resource Allocation:** Fog nodes can dynamically adjust their resources based on the workload, ensuring optimal performance. * **Enhanced Security:** Data is processed locally, reducing the risk of data breaches during transmission to the cloud.

Processes data at multiple levels, including the device, gateway, and cloud. This approach allows for a more flexible and scalable solution, accommodating diverse data sources and processing needs. 2. Data Processing Capabilities – Edge Computing: Limited processing capabilities, primarily focused on basic tasks like image recognition, data filtering, and sensor data analysis.

**1. Cloud Computing:**
– A centralized model where resources are shared among users. – Offers scalability, flexibility, and cost-effectiveness. – Examples: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). **2.

– Smart home devices that adjust lighting or temperature based on user preferences. – The concept of edge computing is based on the processing of data at the edge of the network, closer to the source of data. This allows for faster response times and reduced latency.

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