环境能量驱动的无线传感器节点自适应数据传输机制

发布时间：2018-06-18 05:50

本文选题：环境能量驱动 + 无线传感器网络　；参考：《天津大学》2014年硕士论文

【摘要】：节点能量受限是无线传感器网络(Wireless Sensor Networks,WSNs)的设计及应用技术中的重要问题,尤其在环境恶劣,无法更换电源环境下的WSNs中更为突出。近年来,随着硬件设计技术及环境能量收集技术的发展,节点可以通过能量收集装置收集太阳能、振动能、电磁能等能量,提高节点的续航能力,这催生了环境能量驱动的无线传感器网络(Energy Harvesting Wireless Sensor Networks,EH-WSNs)的出现。环境能量收集过程具有很强的随机性和不确定性,给无线传感器网络设计带来了新的挑战。利用收集的环境能量优化网络和节点性能成为EH-WSNs研究的热点问题。本文考虑环境能量收集过程的随机性和不确定性,研究了传感器节点的数据优化传输机制,主要研究工作如下:(1)根据EH-WSNs节点的能量及数据传输特点,建立了节点的数据传输模型;在已知能量收集情况的前提下,以最大化固定时间T内节点的数据传输量为目标建立了节点传输优化模型,经过理论分析与推导,提出离线数据传输优化算法—前向-后向搜索数据传输优化策略(Forward Backward Searching,FBS策略),实现了数据传输全局最优。(2)利用马尔科夫预测模型,实现了能量收集情况的预测,并且在前向-后向搜索数据传输优化策略的基础上提出自适应的数据传输策略(Adaptive Forward Backward Searching,AFBS策略);该策略在未知能量收集情况的前提下,实时给出数据传输的功率,实现数据传输优化目的。(3)仿真实现并且分析了提出的FBS和AFBS数据传输优化策略。仿真结果表明,前向-后向搜索数据传输优化策略实现了固定时间T内数据传输的全局最优,时间越长优化效果越好;自适应数据传输策略的仿真结果表明,本文提出的自适应算法优于“能量即来即用”的数据传输方法(Energy used up,EUP策略),并且与FBS策略下传输的数据量十分接近。
[Abstract]:Node energy limitation is an important problem in the design and application of Wireless Sensor Networks (WSNs) in wireless sensor networks, especially in the WSNs where the environment is too bad to replace the power supply. In recent years, with the development of hardware design technology and environmental energy collection technology, the node can collect solar energy, vibration energy, electromagnetic energy and other energy through the energy collection device, so as to improve the ability of the node to live. This spawned the emergence of an environmentally energy-driven wireless sensor network, Energy harvesting Wireless Sensor Networks (EH-WSNs). The environmental energy collection process has strong randomness and uncertainty, which brings new challenges to the design of wireless sensor networks. Optimization of network and node performance using collected environmental energy has become a hot issue in EH-WSNs research. In this paper, considering the randomness and uncertainty of the environmental energy collection process, the optimal data transmission mechanism of sensor nodes is studied. The main work is as follows: 1) according to the energy and data transmission characteristics of EH-WSNs node, The data transmission model of nodes is established, and with the premise of known energy collection, the optimization model of node transmission is established with the aim of maximizing the amount of data transmission of nodes within a fixed time T, which is analyzed and deduced theoretically. An off-line data transmission optimization algorithm, forward backward searching algorithm (FBS), is proposed, which realizes the global optimization of data transmission. The Markov prediction model is used to predict the energy collection. On the basis of the forward backward search data transmission optimization strategy, an adaptive forward backward searching strategy is proposed, and the power of the data transmission is given in real time under the condition of unknown energy collection. Data transmission optimization is realized by simulation and the proposed optimization strategies of FBS and AFBS are analyzed. The simulation results show that the optimization strategy of forward-backward search data transmission achieves the global optimization of data transmission in fixed time T, and the longer the time is, the better the optimization effect is, and the simulation results of adaptive data transmission strategy show that, The adaptive algorithm proposed in this paper is superior to the energy used upEUP strategy, and is very close to the amount of data transmitted under this strategy.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP212.9;TN929.5

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