Fog Computing Architecture | Fog Computing Working Operation
This page describes Fog Computing Architecture and Fog Computing Working Operation. The fog computing architecture consists of three layers IoT devices layer, Fog layer and Cloud Layer.
Fog computing is the next generation computing which extends the cloud computing to the edge of the network. It is also known as edge computing. It has been developed to address the issues faced by cloud computing.
As we know volume of data generation is exploding due to huge amount of data generation daily by IoT devices, Sensors, wide amount of internet usage and so on. It is estimated that about 50 billion devices will be online by 2020. The current cloud model is not capable to handle this huge amount of data generated by private companies, factories, airplanes, healthcare devices etc. Moreover data generated by IoT devices are sent to clouds for analysis and storage. After the analysis, the data are sent back to the devices or are used to perform certain action. This increases data bandwidth in the internet highway. Moreover certain time sensitive data can not be handled by cloud network due to its higher latency.
The figure-1 depicts three layers viz. device, fog layer and cloud. As shown fog is intermediate layer between
cloud and devices which generate the data as shown.
Fog computing extends the cloud to be closer to the things which generate
data. This minimizes latency requirement as fog nodes directly act on the data.
It processes and analyzes the data generated by IoT devices. Following are the major functions of
fog computing architecture.
• Analyzes most time sensitive data at the edge of the network, where they are generated by devices. This avoids sending huge amount of data to the cloud.
• It acts on IoT data in milliseconds as per policy.
• Fog computing sends only selected data to the cloud for analysis and long term storage.
Fog Computing Architecture
The Fog computing architecture consists of physical and logical elements in the form of hardware and software to implement IoT (Internet of Things) network. As shown in figure-2, it is composed of IoT devices, fog nodes, fog aggregation nodes with the help of fog data services, remote cloud storage and local data storage server/cloud. Let us understand fog computing architecture components.
• IoT devices: These are devices connected on IoT network using various wired and
wireless technologies. These devices produce data regularly in huge amount. There are numerous wireless technologies used in IoT
which include Zigbee, Zwave, RFID, 6LoWPAN, HART, NFC, Bluetooth, BLE, NFC, ISA-100.11A etc.
IoT protocols used include IPv4, IPv6, MQTT, CoAP, XMPP, AMQP etc.
• Fog Nodes: Any device with computing, storage and network connectivity is known as fog node. Multiple fog nodes are spread across larger region to provide support to end devices. Fog nodes are connected using different topologies. The fog nodes are installed at various locations as per different applications such as on floor of a factory, on top of power pole, along side of railway track, in vehicles, on oil rig and so on. Examples of fog nodes are switches, embedded servers, controllers, routers, cameras etc. High sensitive data are processed at these fog nodes.
• Fog aggregate nodes: Each fog nodes have their aggregate fog node. It analyzes data in seconds to minutes. IoT data storage at these nodes can be of duration in hours or days. Its geographical coverage is wider. Fog data services are implemented to implement such aggregate node points. They are used to address average sensitive data.
• Remote Cloud: All the aggregate fog nodes are connected with the cloud. Time insensitive data or less sensitive data are processed, analyzed and stored at the cloud.
• Local server and cloud: Often fog computing architecture uses private server/cloud to store the confidential data of the firm. These local storage is also useful to provide data security and data privacy.
Fog Computing Working operation
As we know there are three types of data viz. most time sensitive data, less time sensitive data and
time-insensitive data. Fog computing architecture works based on type of data it receives.
Nearest fog nodes takes data input from the devices. Let us understand working of fog computing architecture.
➨Most time sensitive data are handled by nearest fog node to end device which has generated the data. After the received data is analyzed, decision or action is transmitted to the device. After this, fog node sends and stores summary to the cloud for future analysis. The data at fog node is analyzed in fraction of a second.
➨Less time sensitive data are sent to aggregate node for analysis. After analysis is performed, aggregate node sends decision or action to the device through nearest node. Aggregate fog node takes seconds or minutes to complete the analysis. The aggregate node later sends the report to cloud for future analysis purpose.
➨The time insensitive data can wait for longer duration (in hours, days or weeks). The data is sent to cloud for storage and future analysis.
• Also refer advantages and disadvantages of fog computing >> for more information.
Cloud Storage Related Links
Main IoT tutorial
Cloud Storage tutorial
what is cloud storage
Public vs private vs hybrid cloud types
Cloud storage infrastructure
Cloud storage working
traditional cloud vs cloud storage
cloud storage providers
cloud storage security