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Role of Intelligent IOT Applications in Fog paradigm: Issues, Challenges and Future Opportunities

Summary In a world full of digital innovation technologies including 5G wireless, Internet of things, embedded artificial intelligence is developing. There are billions of applications and devices that need to be managed. These are working to measure, monitor, process, analyze and react seamlessly on a huge amount of data. There is a need for a new communication architecture that is to deal with latency, bandwidth, accessibility, rising cost, sensitive data security In today's scenario all the devices are connected to communicate huge and heterogeneous amounts of data. With each new day, the way the world interacts is changing. With the increasing use of sensor and IoT devices, the generation of data is also increasing. With this increased data, the computing and storage is also becoming important. The fathomless placement of smart, interconnected devices is expected to reach 50 billion units by 2020. This exponential rise is fueled by proliferation of networks of mobile devices, smart sensors, wireless sensors and actuators. There is a need for new concepts and technologies to manage this growing squadron of IoT devices. The Internet of everything solutions are connecting every object. This has generated a large amount of data. This amount of data cannot be processed by a centralized cloud environment. There are applications where data needs real‐time response and low latency. The data being sent to the cloud for processing and then coming back to the application generating data can seriously impact on the performance. This delay can cause delays in decision making and this is not bearable in real‐time applications. To handle such scenarios, fog computing emerged as a solution. Fog computing extends the cloud near to the edge of network to decrease latency as well as bandwidth requirements. It acts as an intermediate layer between the cloud and devices generating data

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