Fog Computing vs. Edge Computing?
What's the difference in the Internet of Things (IoT)?
The fundamental objective of the Internet of Things (IoT) is to obtain and analyze data from assets that were previously disconnected from most data processing tools.
This data is generated by physical assets or things deployed at the very edge of the network—such as motors, light bulbs, generators, pumps, and relays—that perform specific tasks to support a business process. The Internet of Things is about connecting these unconnected devices (things) and sending their data to the cloud or Internet to be analyzed.
In traditional IoT cloud architecture, all data from physical assets or things 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 assets 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
- 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 assets 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.
Fog computing
In fog computing, transporting data from things to the cloud requires many steps.
So fog computing involves many layers of complexity and data conversion. Its architecture relies on many links in a communication chain to move data from the physical world of our assets into the digital world of information technology. In a fog computing architecture, each link in the communication chain is a potential point of failure.
Edge computing
Edge computing simplifies this communication chain and reduces potential points of failure.
In edge computing, physical assets like pumps, motors, and generators are again physically wired into a control system where the PAC automates them by executing an onboard control system program. Intelligent PACs with edge computing capabilities collect, analyze, and process data from the physical assets they’re connected to—at the same time they’re running the control system program.
PACs then use edge computing capabilities to determine what data should be stored locally or sent to the cloud for further analysis. In edge computing, intelligence is literally pushed to the network edge, where our physical assets or things are first connected together and where IoT data originates.
Edge computing saves time and money by streamlining IoT communication, reducing system and network architecture complexity, and decreasing the number of potential failure points in an IoT application. Reducing system architecture complexity is key to the success of IIoT applications.
What is the main difference between cloud computing, Internet of Things, Fog Computing and Edge computing ?
Internet of Things (IoT) refers to the network of end points that consist of sensors, actuators etc. that can collect various data & send backward for analysis / processing before sending forward certain control signals for the actuators to take the corrective / preventive actions.
Cloud Computing refers to the intelligence (data analysis & processing capabilities) are reside in the cloud e.g. whether it is on-premises private cloud or public cloud that can be hosted in various data centers in the world.
Both Fog Computing & Edge Computing are more related to IoT whereby intelligence of data analysis & processing power for Fog Computing is at the distributed area / network closer to the IoT sensors & actuators e.g. at the IoT gateways.
Whereas intelligence of data analysis & processing power for Edge Computing is at another layer behind IoT gateways called edge layer to provide certain pre-processing or analytics on data received from IoT sensors etc. These data normally is time critical that is better to be processed at the edge rather than sending back to the data canter(s) / cloud for processing.
To stitch all these terms together - generally we can explain their functions through the IoT data flow for processing: data -> sensors -> IoT gateways (fog computing) -> edge devices (edge computing) -> data centers (cloud computing). You can also refer to the diagram attached. Note: when there is fog computing at IoT gateway level doesn't mean edge / cloud computing is redundant i.e. what they analyze or process at each level is depending on factors like time urgency, how small / big the data packets, nature of the IoT applications etc.
Fog computing versus edge computing
Many use the terms fog computing and edge computing interchangeably, as both involve bringing intelligence and processing closer to where the data is created. However, the key difference between the two is where the intelligence and compute power is placed.
In a fog environment, intelligence is at the local area network. Data is transmitted from endpoints to a gateway where it is then transmitted to sources for processing and return transmission.
In edge computing, intelligence and power of the edge gateway or appliance are in devices such as programmable automation controllers.
I will recommend you to read this blogs :
https://blogs.cisco.com/perspectives/iot-from-cloud-to-fog-computing
Mobile Edge Computing (MEC) is a paradigm that took its first steps in 2009 through the concept of cloudlet. It was proposed as an alternative to Mobile Cloud Computing (MCC), in which resource-constrained mobile devices were offloading intensive tasks up to the distant Cloud. On the contrary, in MEC, mobile devices offload their tasks to resource-rich computers or clusters of computers (i.e., cloudlets) that are topologically closer. Indeed, cloudlets are located AT the network edge (e.g., co-located with a cellular base station or Wi-Fi access point). Looking at its definition, MEC replaces the centralized and distant Cloud and exploits it only as an orchestrator and as a fallback solution when no suitable cloudlets are available in vicinity. ETSI MEC is a standard implementation of MEC to be integrated in the cellular networks, while Edge Computing is just the extension of the MEC concept to address both mobile and fixed devices.
On the other hand, Fog Computing was proposed by Cisco few years later, in 2012. We can say that Fog Computing is a generalization of the MEC paradigm, as it extends the Cloud TOWARD the network edge, distributing resources and services ANYWHERE along the Cloud-to-Things continuum, in topological proximity to the end devices requiring them. Therefore, the main difference is that the Fog conceives the possibility to have a hierarchy of Fog nodes that may potentially span from the end devices, to the edge, through the core, and up to the Cloud. The overall service/application may be then decomposed and deployed in components within such a hierarchy. Each node in the hierarchy will play its role, and this mainly depends on its position/layer within this pyramid-like organization. Thanks to this characteristic, the Fog perfectly suits the needs of the Internet of Things (which may be characterised by wide-area deployments and complex applications requiring the characteristics of both the Fog and the Cloud). Nonetheless, Fog Computing is generic enough to satisfy the requirements of many other verticals (e.g., augmented reality, gaming, content delivery) that are not strictly related to IoT.
Dear Hafizur Rahman ,
Related to IoT and CC you can you can also refer to my modern paper which contains complete and detailed information:
Nidhal Kamel Taha El-Omari, “Cloud IoT as a Crucial Enabler: a Survey and Taxonomy”, Modern Applied Science, The Canadian Center of Science and Education, published by Canadian Center of Science and Education, Canada, p-ISSN: 1913-1844, e-ISSN: 1913-1852, DOI:10.5539/mas.v13n8p86, 13(8):86-149, 2019.
Or simply you can click here:
https://www.researchgate.net/publication/334725286_Cloud_IoT_as_a_Crucial_Enabler_a_Survey_and_Taxonomy
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