Task Mapping based In-network Processing in Ubiquitous Healthcare System

Abstract

Ubiquitous healthcare system is a system capable of monitoring the biomedical signals of a patient wirelessly by using wireless sensor network. Biomedical signals are measured using biomedical devices and transmitted to the base station by using wireless sensor network. However, studies shows that with the increment of the number of users accessing the same system simultaneously have causes traffic overload issue at the base station of the system. This is caused by the continuous large number of data packets transmitting from the sensor node to the base station. Due to the traffic overload issue, base station and its nearby relay sensor nodes are not able to receive and analyze the data packet in timely manner and causes data packet loss issue. Hence, in-network processing is adapted in order to resolve this issue. In-network processing is the collaboration among sensors through parallel processing mechanisms to achieve high processing power in wireless sensor networks. A threshold-based tri-axial accelerometer fall detection algorithm is implemented by adapting in-network processing inside the system. Calculation algorithms and decision algorithms are executed inside the sensor node to reduce the number of required data transmission from the sensor node to the base station. Research result shows that by implementing in-network processing, overall processing power for the system increased significantly. System analysis also shows that by adapting this method, traffic over-load issue can be avoided and data packet loss is successfully reduced.