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Comparisons of maximum system lifetime in diverse scenarios for body sensor networks

机译:人体传感器网络在各种情况下的最大系统寿命比较

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In this paper, the main target is to compare the system lifetimes in diverse scenarios based on our new energy dissipation model in the body sensor network as well as maximize the system lifetime of sensor nodes when they will make communication among body sensors and personal communication unit. Nowadays, the ultra low energy consumption is the very much important challenge for medical applications. The best compression technique like LPC is selected for energy saving based on some calculations. This research work studies and analyzes the transceiver energy consumption for different compression algorithms and select the best technique like LPC for energy saving. Formulation of a linear programming problem is also the important part of this research work, where is to maximize the system lifetime which is equivalent to the time until the first node runs out of battery. Maximum system lifetimes are calculated by MATLAB optimization technique using and without using efficient compression algorithm like LPC in various environments. Results show that maximum system lifetimes calculated in different scenarios using efficient compression technique like LPC is better than without using compression technique.
机译:本文的主要目标是基于我们在人体传感器网络中的新能量耗散模型,比较各种场景下的系统寿命,以及在传感器节点在人体传感器和个人通信单元之间进行通信时最大化传感器节点的系统寿命。 。如今,超低能耗已成为医疗应用中非常重要的挑战。根据一些计算,选择了最佳压缩技术(如LPC)来节能。这项研究工作针对不同的压缩算法研究和分析了收发器的能耗,并选择了LPC之类的最佳技术来节能。制定线性规划问题也是这项研究工作的重要部分,在该研究中,最大程度地延长系统寿命,这相当于直到第一个节点用完电池为止的时间。通过使用和不使用像LPC这样的高效压缩算法的MATLAB优化技术,可以在各种环境中计算出最大的系统寿命。结果表明,使用像LPC这样的高效压缩技术,在不同情况下计算出的最大系统寿命要比不使用压缩技术时更好。

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