Efficient Healthcare Assisting Cloud Storage Strategy using Fog Prioritization Logic based on Edge Devices

Abstract

In recent years there are many researchers conducted regarding with cloud storage benefits and its efficiency improvements, but all are raising a question regarding the effectiveness and privacy. The effectiveness of the cloud storage system purely depends on the storage capacity and responsiveness of the server, in which the size of the data is large automatically the responsiveness of the storage server goes down. To avoid this issue many researchers found a lots of solution such as multiple cloud server placements, the local cloud farm fixation and so on. But all are coming too struck with the privacy issues and the security threats are more in the case of such things. These issues need to be resolved with one powerful mechanism as well as providing a good storage mechanism without any security threats. In this paper, a healthcare application is taken into consideration and introduce a new fog based cloud storage system is designed such as Intelligent Fog based Cloud Strategy using Edge Devices (IFCSED), in which this Fog Computing process provides an efficient health data storage structure to the cloud server to maintain the high priority records without considering on regular or non-prioritized records. This proposed strategy follows Edge-based Fog assistance to identify the healthcare data priority utilizing analyzing the records, identify the priority level and classify those priority records from the data and pass that to the remote cloud server as well as keep the remaining non-prioritized records into the local fog server. The fog server data can be back up with every point of interval using data backup logics. These backup assures the data protection and the integrity on the storage medium as well as the proposed approach of IFCSED eliminates the processing delay by using time complexity estimations. The data which is coming from Internet of Things (IoT) based real-world health record will be acquired by using controllers and other related devices, which will be delivered to the Edge Devices for manipulation. In this Edge processing device accumulates the incoming health data and classifies that based on the prioritization logic. The health sensor data which is coming in regular interval with normal sensor values are considered to be the regular non-prioritized data and the health sensor data coming up with some abnormal contents such as mismatched heart rate, increased pressure level and so on are considered as a the prioritized record. The sensor assisted health data will low-priority will be moved to the fog server, which is locally maintained into the environment itself and the sensor assisted health data coming up with high priority will be moved into the remote cloud server. The proposed approach assures the time efficiency, reduction in data loss, data integrity and the storage efficiency, as well as these things, will be proved over the resulting sections with proper graphical results.