Mapping of sensor nodes with servers in a mobile Health-Cloud environment

Body-sensors such as accelerometers, oximeters and arm cuff based monitoring systems are used to sense patients' health conditions. Any abnormal behavior of patient's data triggers an alert signal to the health-centers to take action. In this paper, we address the problem of mobile patients' health monitoring using Health-Cloud. When a patient changes his/her location from one place to another, the associated default gateway changes. With the change in the gateway connected to the health-cloud, the optimum mapping between the server and the mobile node also changes. We propose an optimal resource allocation framework for health-cloud to monitor patients' health conditions when they change locations. To optimize the resource allocation problem and provide an optimum mapping between the mobile node and the server, we use an auction theory based solution approach. We evaluate the performance of the proposed scheme numerically. The experimental results show that we receive 20%, 58%, and 61% more utility for the three different cases with respect to the default mapping.