The Study Of DVS Strategy Of Intelligent Terminal For Health Monitoring

With the continuous development of networking, communications andmicroprocessor chip technology as well as the emphasis on health care, a new healthservice model emerges: wireless health monitoring. Wireless health monitoring system iscomposed of three parts: the wireless body area network (WBAN), the local intelligentterminal and the remote service center. The smart terminal is an embedded system, whichcan processes health data intelligently and has high requirements both in areas of the real-time and the power consumption. Intelligent terminal power consumption can bereduced by both static technology and dynamic technology. However, static technologycan’t fully meet the power consumption of the system, the current studies are focused onthe dynamic low-power technology, the DPM (Dynamic Power Management) and DVS(Dynamic Voltage Scaling).DVS is a technique that sacrifices performance of the system to save energy. Most ofthe DVS scheduling algorithms tend to slow the speed of processing the event, the slowerthe better, rather than consider timing constraints. Based on the analysis of dynamicvoltage scaling and adaptive DVS scheduling policy, according to the intelligent terminalload predictability, both power and timing requirements, and dynamic selection of activeonline DVS scheduling and negative DVS scheduling policy, improve the adaptivescheduling for the intelligent terminal working characteristics.First analyzes the beneficial characteristics of the adaptive DVS scheduling policywith the power, timing. Followed by improved DVS scheduling policy used in theintelligent terminal, use the maximum amount of data of ECG data to verify the actuallow-power characteristics of the strategy. The results show that the adaptive DVSstrategy can reduce the power consumption of4.2%of the entire intelligent terminal,improved DVS strategy can be to reduce6.5%of the power of the intelligent terminal.