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Fog and Edge Computing

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(US Navy Blue Angels, San Francisco Fleet Week 2014 - Jeff M. Wang)

- Fog Computing

Fog computing is a new computing mode. As a derivative of cloud computing, fog computing can solve the problems of high latency, overloaded center server and overloaded bandwidth of network.

"Pushing computing, control, data storage and processing into the cloud has been a key trend in the past decade. However, cloud alone is encountering growing limitations in meeting the computing and intelligent networking demands of many new systems and applications. Local computing both at the network edge and among the connected things is often necessary to, for example, meet stringent latency requirements, integrate local multimedia contextual information in real time, reduce processing load and conserve battery power on the endpoints, improve network reliability and resiliency, and overcome the bandwidth and cost constraints for long-haul communications.

The cloud is now "descending" to the network edge and sometimes diffused onto end user devices, which forms the "fog". Fog computing distributes computing, data processing, and networking services closer to the end users along the cloud-to-things (C2T) continuum. Instead of concentrating data and computation in a small number of large clouds, fog computing envisions many fog systems deployed close to the end users or where computing and intelligent networking can best meet user needs. Fog computing and networking present a new architecture vision where distributed edge and user devices collaborate with each other and with the clouds to carry out computing, control, networking, and data management tasks.

Realizing fog computing and networking imposes many new challenges. For example, how to compose, deploy, and manage distributed fog services, how to enable highly scalable and manageable fog networking and computing, how to secure fog computing systems, how should the fog interact with the cloud, and how to enable users to control their fog services provided by fog operators. Addressing these challenges necessitates rethinking of the end-to-end network and computing architecture. " -- [FOG WORLD CONGRESS] 


- Edge Computing

"Edge computing is the conversion of IoT data to usable information using microprocessors collocated with the sensor, or at the edge of the network. Edge computing reduces network bandwidth, data storage, and analysis requirements. The price is increased power at the mobile device, requiring innovations in energy harvesting and storage. Innovations in edge computing will accelerate new developments across a wide array of applications." -- [IEEE Computer Society]


The Key Difference Between Fog Computing and Edge Computing


In traditional IoT cloud architecture, all data from physical things (devices) is transported to the cloud for storage and advanced analysis. Once in the cloud, the data is used for cognitive prognostics (that is, predictive maintenance, forensic failure analysis and process optimization). 

Fog and edge computing in manufacturing and automation applications are network and system architectures that attempt to collect, analyze, and process data from these things (devices) more efficiently than traditional cloud architecture. These architectures share similar objectives: to reduce the amount of data sent to the cloud, to decrease network and Internet latency, and to improve system response time in remote mission-critical applications. 

However, there is a key difference between the two concepts. Both fog computing and edge computing involve pushing intelligence and processing capabilities down closer to where the data originates—at the network edge. The key difference between the two architectures is exactly where that intelligence and computing power is placed. 

  • Fog computing pushes intelligence down to the local area network (LAN) level of network architecture, processing data in a fog node or IoT gateway.
  • Edge computing pushes the intelligence, processing power, and communication capabilities of an edge gateway or appliance directly into devices like PACs (programmable automation controllers). 

In both architectures data is generated from the same source—physical things such as pumps, motors, relays, sensors, and so on. These devices perform a task in the physical world such as pumping water, switching electrical circuits, or sensing the world around them. These are the “things” that make up the Internet of Things.



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