Abstract
In recent years, cloud-assisted body area network (CABAN) technologies have made their entrance in the Smart healthcare field, such as Smart home environment, and play a significant role for healthcare data storage, processing, and efficient decision making. However, currently, the CABAN paradigm in the healthcare domain is facing increasing difficulty in handling the huge amount of sensor data that the body sensor devices generate from diverse Smart home applications. Therefore, the challenging is now timely storing, processing, and analyzing of the sensor data in real time to maintain the Quality of Service (QoS) requirements of the caregivers or Smart home applications. QoS, here, is the capacity to support diverse Smart home applications in healthcare with different priorities, performance, and resource requirements. Therefore, in this paper, we present a fast and robust cloud resource allocation model for body sensor devices to ensure QoS for Smart home healthcare applications. We develop the proposed resource allocation algorithm using agent-based modeling (ABM) and ontology. There are few works, which consider ABM and ontology for resource allocation in CABAN platform. Moreover, we used an ABM tool called NetLogo to implement the proposed resource allocation model. The results from the implementation were compared with the results of existing algorithms and found to be promising.