Fog Computing advantages and applications

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Fog and Cloud

What is fog and cloud computing?
Fog:
The fog computing is an extension of cloud computing services to the edge of the network. Fog is a virtualized environment to provide computation, storage and networking services connecting the IoT devices and core cloud.

Cloud:
The Cloud computing provides centralized computing, storage and processing environment for various applications with ubiquitous, on-demand network access. Cloud enables data processing of an application in the core cloud, which benefits the application designer to utilize non application oriented accepts (consistency, availability and storage of data).

How Fog and cloud are different?
The processing and analysis in cloud computing requires all application data to be transmitted to cloud that needs a large bandwidth and heavy energy consumption. Although, providing the required resources latency in decision making is inevitable.

The Fog computing extends the cloud computing services in close proximity of the end users i.e. edge of the network. Fog computing provides distributed computing (storage and processing) platform to end devices, which optimizes the bandwidth and energy consumption.

Advantages for fog computing?

Distributed Computing:
Fog computing provides geographically distributed environment with limited resources and cloud as backhaul network for analysis and processing unit for huge velocity of data.

Heterogeneity: The smart objects in Fog environment are of wide variety that produces periodic data, streaming data etc.

Features: Edge Location, Low Latency, Location awareness

Applications: Real-time and low latency applications: Live streaming, AR Gaming, Smart Traffic Monitoring, smart parking, smart grid, smart home, smart vehicles, smart healthcare etc.

Challenges:  Latency (Data aggregation, Resource Provisioning,  mobility), Reliability, network management, security and privacy.

Research Issues:
Fog Networking (SDN and NFV), QoS (Connectivity, Reliability, Resource Management and Delay), computation offloading,  price and demand monitoring.

An example scenario of Fog computing:

In a smart city, with rapid growth and highly influencing Information Communication Technology (ICT) the primary concern of human and machines is low-latency services. Fog computing can withstand and address the issue as its platform enables non-trivial cloud computing environment to smart entities (IoT enabled devices, smart sensors etc.). For Example in a smart grid plays a vital role in a smart city for sustainability and optimality of energy consumption in the grid. The data accumulated from various smart devices like smart meters, smart appliances, smart home, smart Plug-in Hybrid Vehicles (PHEVs) and the grid itself generate enormous data, the data processing, computing and service information response is time critical. Fog computing can address this issue as it can provide the smart grid services in a distributed computing model and cloud as the core platform for data analysis and prediction analysis.

Difference between different types of computing: 



https://link.springer.com/chapter/10.1007/978-981-10-5861-5_5

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