A cloud-based interference-aware remote health monitoring system for non-hospitalized patients

Distance health monitoring is becoming an attractive option for both the patients and the medical sector staff. However, these systems face many design challenges including the large amount of processed data, users´ mobility, and network coverage area. Accordingly, integrating cloud computing with Wireless Body Area Networks (WBANs) is amongst the best solutions to promote health monitoring systems. In this paper, we propose a cloud-based real-time remote health monitoring system. Several novel techniques are developed to optimize the performance of the proposed system. First, we utilize the concept of data classification and aggregation to reduce the traffic flow in the cloud. Second, a dynamic channel assignment policy is developed to distribute the users´ WBANs among the available frequency channels to manage interference. Third, to optimize the delay of the delivered data a delay-aware routing metric is proposed to be used in the multi-hop routing. In addition, this metric is further utilized by the association protocols used by the WBANs to connect with the cloud. The simulation results prove the efficiency of the proposed architecture in optimizing the end-to-end delay, managing interference, maximizing the network capacity, and tracking the mobility of the users.