What is fog computing? List the characteristics of fog computing.

Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. The term fog computing comes from the metaphor that a fog, unlike a cloud, is close to the ground.

Characteristics of fog computing include:

1. Low latency and location awareness: Fog computing can provide lower latency because it reduces the amount of data that is transported to the cloud for processing, analysis and storage. This is often critical in scenarios such as telemedicine and patient care, where milliseconds can have significant impact.

2. Geographical distribution: Fog networks can be geographically distributed to cover a large area, which is not typically possible with traditional cloud architectures.

3. Real-time data processing: Fog computing can analyze and process data in real time or near real time. This is particularly useful in time-sensitive processes and can lead to more efficient decision-making.

4. Mobility support: Fog computing supports mobile computing, mobile networking, and seamless handovers for mobile devices moving across different networks or locations.

5. Interoperability: Fog computing supports standard and open APIs, which means it can work with a wide range of protocols and can integrate with different hardware and software systems.

6. Security: Because data can be processed locally in fog computing, it can potentially lead to improved security as less sensitive data needs to be transported over the network.

Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. It essentially extends cloud computing and services to the edge of the network, bringing the advantages and power of the cloud closer to where data is created and acted upon.

Characteristics of fog computing include:

1. Low Latency and Location Awareness: Fog computing can provide lower latency because it reduces the amount of data that is transported to the cloud for processing, analysis and storage. This is particularly important in big data analytics and real-time applications. Also, fog computing can provide location awareness services.

2. Real-time Data Processing: Fog computing can analyze most data at the network's edge, only sending the necessary data to the cloud, which can improve efficiency and reduce the amount of data that needs to be transported to the cloud for processing, analysis and storage.

3. Mobility Support: Fog computing supports mobile computing and IoT devices, including the ability to provide seamless mobility and manage the dynamic location of these devices.

4. Interoperability: Fog computing can work with different standards and protocols and can communicate with the cloud and other edges.

5. Distributed Processing and Networking: Fog computing involves creating a network architecture that allows for distributed computing, storage and networking in a way that's efficient and scalable.

6. Security: Fog computing can improve security by using a distributed approach to process and analyze data, which can make it harder for attackers to gain access to the data.

Fog computing, also known as fog networking or fogging, is a decentralized computing infrastructure in which data, compute, storage and applications are distributed in the most logical, efficient place between the data source and the cloud. It essentially extends cloud computing and services to the edge of the network, bringing the advantages and power of the cloud closer to where data is created and acted upon.

Characteristics of fog computing include:

1. Low Latency and Location Awareness: Fog computing can provide lower latency because it reduces the amount of data that is transported to the cloud for processing, analysis and storage. This is particularly important in big data analytics and real-time applications. Also, fog computing can provide location awareness services.

2. Real-time Data Processing: Fog computing can analyze most data at the network's edge, only sending the necessary data to the cloud, which can improve efficiency and reduce the amount of data that needs to be transported to the cloud for processing, analysis and storage.

3. Mobility Support: Fog computing supports mobile computing and IoT devices, including the ability to provide seamless mobility and manage the dynamic location of these devices.

4. Interoperability: Fog computing can work with different standards and protocols and can communicate with the cloud and other edges.

5. Distributed Processing and Networking: Fog computing involves creating a network architecture that allows for distributed computing, storage and networking in a way that's efficient and scalable.

6. Security: Fog computing can improve security by using a distributed approach to process and analyze data, which can make it harder for attackers to gain access to the data.