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' 'FOG COMPUTING.pdf and it is useful for ucha
- 2. CONTENTS: 1. DEFINTION 2. COMPONENTS 3. BEST PRACTICES 4. TYPES 5. ARCHITECTURE 6. PROS AND CONS 7. APPLICATIONS 8. CONCLUSION
- 3. DEFINITION Fog computing is a type of computing where data and applications are stored and processed closer to the devices that generate the data, rather than in a centralized cloud. Introduced by Cisco, this approach helps improve the performance and efficiency of cloud computing by handling tasks locally, closer to the source of the data. It's also known as fogging or edge computing and ensures smooth operation between your devices and big data centers.
- 4. 1. Physical & virtual nodes (end devices): These devices are data generators and can span a large spectrum of technology. 2. Fog nodes: Fog nodes are independent devices that pick up the generated information. 3. Monitoring services: Monitoring services usually include application programming interfaces (APIs) that keep track of the system’s performance and resource availability. 4. Data processors: Data processors are programs that run on fog nodes. 5. Resource manager: Fog computing consists of independent nodes that must work in a synchronized manner. 6. Security tools: Security must be built into the system even at the ground level. 7. Applications: Applications provide actual services to end-users.
- 5. Top 10 Fog Computing Best Practices to Follow
- 6. Four Types of Fog Computing. The four main types of fog computing are mentioned below. •Device-level fog computing runs on devices such as sensors, switches, routers, and other low-powered hardware. It can be used to gather data from these devices and send it to the cloud for analysis. •Edge-level fog computing runs on servers or appliances located at the edge of a network. These devices can be used to process data before it is sent to the cloud. •Gateway-level fog computing runs on devices that act as a gateway between the edge and the cloud. These devices can be used to manage traffic and ensure that only relevant data is sent to the cloud. •Cloud-level fog computing runs on servers or appliances located in the cloud. These devices can be used to process data before it is sent to end users.
- 7. Hierarchical Fog Computing Architecture •IoT layer: This layer comprises IoT devices, such as sensors or smartphones. •Fog layer: Composing many fog nodes, this layer is the core of the fog computing architecture. •Cloud layer: This layer is mainly composed of the centralized cloud infrastructure.
- 8. ADVANTAGES ➢ Privacy Fog computing can be used to control the extent of privacy ➢ Productivity If customer needs to make the machine function according to the way they want, they can utilize fog applications. ➢ Security Fog computing has the capability to connect multiple devices to the same network. ➢ Bandwidth The bandwidth required for transmitting data can be expensive depending upon the resources ➢ Latency Another benefit of processing selected data locally is the latency savings.
- 9. DISADVANTAGES ➢ Complexity Due to its complexity, the concept of Fog computing can be difficult to understand. ➢ Power Consumption The number of fog nodes present in a fog environment is directly proportional to the energy consumption of them. ➢ Deployment and Configuration Complexity: Deploying fog nodes in diverse and potentially remote locations can be logistically challenging. ➢ Maintenance Unlike cloud architecture, where maintenance is made seamless, it is not so in fog.
- 10. FOG COMPUTING USE CASES Even though fog computing is anticipated to grow at a rapid rate, it is still a technology that is most popular within industries that need data close to the network edge. •Hospitality •Retail •Wearables •Smart buildings •Agriculture •Government •Military
- 11. Fog computing is an exciting development in technology that addresses the need for data processing and storage closer to the data source, such as sensors and smart devices, rather than relying solely on centralized data centers. By placing computation and data storage at the edge of the network, fog computing significantly reduces latency and improves performance for tasks that require real-time responses. This is particularly beneficial for applications in smart cities, healthcare, industrial automation, and the Internet of Things (IoT), where rapid data processing and minimal delay are critical. CONCLUSION
- 12. THANK YOU