Press release
Fog Computing Market Growth, Demand and Technology Research 2017-2027
The objective of fog computing is to improve efficiency and the amount of data transferred to the cloud for processing, analysis and storage. This is most commonly done to improve efficiency, but it may also be used for security and compliance reasons. Popular fog computing applications include: smart city, smart grid, smart buildings, software- defined networks and vehicle networks.The key difference between fog computing and edge computing is where the intelligence and compute power is placed. In a fog environment, intelligence is placed 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. Whereas, in edge computing, intelligence and power of the edge gateway or appliance are in devices such as programmable automation controllers.
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Usually cloud computing is not a viable option for internet of things (IoT), in such cases fog computing is used. Fog Computing’s distributed approach attends to the needs of IoT and industrial IoT, as well as the immense amount of data smart sensors and IoT devices generate, which would be costly and time-consuming to send to the cloud for processing and analysis. Fog computing reduces the bandwidth needed and reduces the back-and-forth communication between sensors and the cloud, which turns out to be beneficial to IoT performance.
Fog Computing Market: Drivers and Challenges
Fog computing market has recently gained importance due to increasing adoption of internet of things worldwide, increasing demand for computing capability at the edge, mainstreaming of cloud computing and high adoption of smart sensors that will create huge amount of data. The growing government and private funding across the globe for research and development in IoT, cloud and fog, and scope for innovative cross-domain applications provide significant growth opportunities in the fog computing market.
The challenges faced by fog computing market are existing data protection mechanisms such as encryption fails to secure data from attackers. Fog computing also does not verify whether the user is authorized or not.
Fog Computing Market: Segmentation
Segmentation on the basis of component:
Hardware
Servers
Switches
Routers
Gateways
Controller
Software
Customized application software
Fog computing platform
Segmentation on the basis of application:
Smart Energy
Building and Home Automation
Smart Manufacturing
Connected Health
Transportation and Logistics
Security and Emergency System
Fog Computing Market: Recent Contracts/Deals and Acquisitions
Few of the recent contracts/deals and acquisitions in Fog Computing market are listed below:
In November 2016, Cisco Systems, Inc. completed the acquisition of ParStream Inc. (provider of analytics database in Germany) in order to enhance the ability of the company to provide analytics at networks edge
In October 2016, Intel Corporation launched new Intel Atom processor E3900 series to enable next generation of smart and connected IoT devices
In September 2016, Microsoft Corporation introduced new services and products spanning security, productivity, intelligence and the cloud in order to make it easier for IT professionals to drive digital transformation throughout their organizations
In September 2016, SAP SE acquired PLAT ONE (enterprise-grade Internet of Things (IoT) solution platform provider) in order to make it easy for enterprises and system integrators to build IoT-enabled applications
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Fog Computing Market: Regional Overview
Fog Computing market is currently dominated by North America region due to countries such as U.S. and Canada taking initiatives to encourage the adoption of internet of things. Europe fog computing market follows next as various industry verticals are realizing the importance of shifting to internet of things and fog computing. APEJ and MEA regions are fast picking up pace in the fog computing market owing to increase in awareness of making use of this technology over cloud computing.
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