The edge analytics market is estimated to grow from USD 1.94 billion in 2016 to USD 7.96 billion by 2021, at a Compound Annual Growth Rate (CAGR) of 32.6%.
Source: Markets and Markets
What value do Fog Computing to companies?
By adding the capability to process data closer to where it is created, fog computing seeks to create a network with lower latency, and with fewer data to upload, it increases the efficiency at which it can be processed.
There is also the benefit that data can still be processed with fog computing in a situation of no bandwidth availability. It provides an intermediary between these IoT devices and the cloud computing infrastructure that they connect to, as it is able to analyze and process data closer to where it is coming from, filtering what gets uploaded up to the cloud.
What are the benefits of Fog Computing in real-time applications?
It is broadly used in IoT applications which involves real-time data. It acts as an extended version of cloud computing. It is an intermediate between the cloud and end users (closer to end users). It can be used in both the ways, that can be between machine and machine or between the human to machine.
- Mobile Big Data Analytics
- Water Pressure at Dams
- Smart Utility Service
- Health Data
What are the major challenges in Fog Computing?
Security challenges are predominant in fog computing.
Fog computing considers the architecture of SOA. The network layer is established between the service layer and the application layer. Hence, Fog computing is designed ahead of traditional networking components, which are highly vulnerable security attacks.