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Mobile Edge Aided Data Dissemination for Wireless Healthcare Systems | IEEE Journals & Magazine | IEEE Xplore

Mobile Edge Aided Data Dissemination for Wireless Healthcare Systems


Abstract:

Recent advances in microelectronic technologies have enabled the design and proliferation of low-power wireless networks for autonomously monitoring and control of wirele...Show More

Abstract:

Recent advances in microelectronic technologies have enabled the design and proliferation of low-power wireless networks for autonomously monitoring and control of wireless healthcare systems. In order to control and update the network nodes (e.g., bug fixing, command distribution, software update) in the healthcare system, reliable and efficient data dissemination is one of the key building blocks. However, traditional data dissemination relies mainly on the Internet of Things (IoT) nodes and thus much energy is wasted. With the development of 5G communication technologies, especially the mobile edge computing (MEC), it is believed that the edge server will become promising and more pervasively deployed. Despite computational offloading, the edge servers are also capable of communicational offloading. Therefore, to achieve data dissemination in an efficient way, we propose an edge-aided data dissemination system, in which the mobile edge servers are used to disseminate different segments of data objects. After that, IoT nodes exchange segments with each other to collect the entire data objects. In our work, we design the installation mechanism and data propagation protocol to not only ensure integrality of the data objects transmitted but also avoid the transmission conflicts. Furthermore, we design an adaptive protocol to achieve efficient data dissemination for heterogeneous IoT networks. We conduct extensive experiments and large-scale simulations. The results demonstrate that with the help of mobile edge servers, the energy efficiency is significantly improved compared to traditional dissemination approaches.
Published in: IEEE Transactions on Computational Social Systems ( Volume: 6, Issue: 5, October 2019)
Page(s): 898 - 906
Date of Publication: 19 June 2019

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