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    Novel adaptive transmission protocol for mobile sensors that improves energy efficiency and removes the limitation of state based adaptive power control protocol (SAPC)

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    Abstract
    In this paper, we have presented a novel transmission protocol which is suited for battery-powered sensors that are worn by a patient when under medical treatment, and allow constant monitoring of health indices. These body-wearable sensors log data from the patient and transmit the data to a base-station or gateway, via a wireless link at specific intervals. The signal link quality varies because the distance between the patient and the gateway is not fixed. This may lead to packet drops that increase the energy consumption due to repeated retransmission. The proposed novel transmission power control protocol combines a state based adaptive power control (SAPC) algorithm and an intelligent adaptive drop-off algorithm, to track the changes in the link quality, in order to maintain an acceptable Packet success rate (PSR)(~99%). This removes the limitation of the SAPC by making the drop-off rate adaptive. Simulations were conducted to emulate a subject’s movement in different physical scenarios—an indoor office environment and an outdoor running track. The simulation results were validated through experiments in which the transmitter, together with the sensor mounted on the subject, and the subject themselves were made to move freely within the communicable range. Results showed that the proposed protocol performs at par with the best performing SAPC corresponding to a fixed drop-off rate value.
    Citation
    Journal of Sensor and Actuator Networks, 2017, 6 (3), pp. 1 - 13 (13)
    Date
    2017-03-15
    Author
    Basu, D
    Sen Gupta, G
    Moretti, G
    Gui, X
    Rights
    Creative Commons Attribution License 4.0
    Publisher
    MDPI AG
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    Copyright © Massey University
    Contact Us | Send Feedback | Copyright Take Down Request | Massey University Privacy Statement
    DSpace software copyright © Duraspace
    v5.7-2020.1