Application of Fog and Cloud Computing for Patient's Data in the Internet of Things

The last few years have brought a sudden boost in the Internet of Things (IoT). It is considered to be the next big thing in the evolution of the Internet and an integral part of the future Internet. IoT devices that have their own storage and processing capabilities can process and store data at their end. However, the devices which don't have storage and processing resources, like sensors attached to the patient's body, collect data from the physical environment and send to some sink for processing and storage. Such sensors generate a huge amount of data, so there is a need to process and store the data efficiently. However, the cloud computing which is used as a platform for IoT has an inherent problem of latency which can cause bad monitoring and patients which need an immediate treatment can be affected. This problem can be considered in every latency sensitive application which requires real-time monitoring and processing. To solve such problems, we need a new platform for IoT related data which offers the same services as a cloud but do not have problems like a cloud. This study proposes a new solution for IoT patient's data which utilizes an intermediate layer, fog computing with cloud computing, and accelerates the awareness and response to events by removing a round trip delay to the cloud for analysis. It also offloads the gigabytes of network traffic from the core network to the local edge fog network. This work also proposes how energy efficient sensing will be done. Implementation based analysis is performed to demonstrate the performance of the proposed solution with existing solutions. Results show reduction of the delay and energy efficient sensing.