论文标题
生长：实时局部数据压缩以支持WBAN的能源效率
GROWN: Local Data Compression in Real-Time To Support Energy Efficiency in WBAN
论文作者
论文摘要
无线技术的演变使得为医疗保健监测的多种目的创建网络。无线身体区域网络（WBAN）可实现对生理信号的连续和实时监控，但是该监视会导致数据传输过多，并极大地影响了设备的功耗。尽管有减少能源消耗的方法，但其中许多并不考虑信息冗余以减少功耗。本文提出了一种局部数据压缩的混合方法，称为“生长”，以减少数据传输过程中的信息冗余并减少能耗。我们的方法结合了WSN中发现的局部数据压缩方法。我们通过实验评估了增长，结果表明，设备的能源消耗减少和网络寿命的增加。
The evolution of wireless technologies has enabled the creation of networks for several purposes as health care monitoring. The Wireless Body Area Networks (WBANs) enable continuous and real-time monitoring of physiological signals, but that monitoring leads to an excessive data transmission usage, and drastically affects the power consumption of the devices. Although there are approaches for reducing energy consumption, many of them do not consider information redundancy to reduce the power consumption. This paper proposes a hybrid approach of local data compression, called GROWN, to decrease information redundancy during data transmission and reduce the energy consumption. Our approach combines local data compression methods found in WSN. We have evaluated GROWN by experimentation, and the results show a decrease in energy consumption of the devices and an increase in network lifetime.
