基于博弈论的物联网能量效率分布式优化研究

发布时间：2018-05-17 08:02

本文选题：物联网 + 无线传感器　；参考：《浙江工商大学》2017年硕士论文

【摘要】：物联网的快速发展,为现代社会提供了以万物互联为基础的巨大信息交互平台,是互联网时代信息获取和共享的更进一步的发展。而无线通信的高速发展,为物联网实现更大规模的信息感知、随时随地的信息交互提供了支撑,相比于有线通信模式下的网络,无线通信支撑下的物联网真正使得万物互联迅速的走进了人们的生活,渗透到每一个人生活的方方面面,渗透到每一个人日常行为的随时随地。然而,无线模式下的物联网运作模式在享受灵活性、移动性等巨大好处的同时,也受到有限能量的严重制约。无线传感器或者是无线手持终端等物联网中普遍使用的设备都遇到电池能量这个瓶颈问题。所以,物联网中无线设备的能量使用效率问题成了当前研究的一个热点,具有很强的现实意义。本文针对物联网中无线设备的能效优化问题展开研究。重点在于对分布式系统的能量效率进行系统级的整体优化。主要研究内容如下:第一,针对物联网中各个用户为了提高能量效率需要科学选择无线通信频率信道的问题,本文提出了基于博弈论的能量优化数学模型,设计了利于系统能量效率优化的效用函数,证明了所提出的博弈模型是精确势能博弈,博弈模型的最佳均衡状态就是系统能量效率最优状态。然后提出了相对应的学习算法,使得系统经过一定步骤的学习迭代,实现了理论分析中的最佳均衡状态,获得了系统能量效率最优的稳定解,实现系统能量效率的全局最优。第二,针对物联网中无线传感器节点信息需要选择合适的骨干网接入点进行能效优化的问题,本文首先建立了传感器节点自由选择接入点问题系统级能量优化的数学模型,然后提出了基于合作概念的博弈模型和相应的效用函数,经过理论分析,证明了最佳的接入点分配方案就是所提出的博弈的最佳均衡点。然后提出了非相关并行学习算法,根据该算法,系统可经过学习以很高的概率收敛到最佳均衡点,也就是所提出系统能效优化问题的最优解,实现系统能量效率的全局最优。
[Abstract]:The rapid development of the Internet of things provides a huge information exchange platform based on the interconnection of all things for the modern society. It is a further development of information acquisition and sharing in the Internet era. The rapid development of wireless communication provides a support for the Internet of things to realize a larger scale of information perception, anytime and anywhere information interaction, compared with the wired communication mode of the network, The Internet of things supported by wireless communication really makes everything interconnect into people's life quickly, permeate every aspect of people's life, permeate every person's daily behavior anytime and anywhere. However, the Internet of things operating mode in wireless mode, while enjoying the great benefits of flexibility and mobility, is also severely restricted by limited energy. Wireless sensors or devices commonly used in the Internet of things, such as wireless handheld terminals, encounter the bottleneck of battery power. Therefore, the energy efficiency of wireless devices in the Internet of things has become a hot topic, which has a strong practical significance. In this paper, the energy efficiency optimization of wireless devices in the Internet of things is studied. The emphasis is on the overall optimization of the energy efficiency of distributed systems at the system level. The main research contents are as follows: first, in order to improve the energy efficiency of the Internet of things, every user needs to choose the wireless communication frequency channel scientifically, this paper proposes a mathematical model of energy optimization based on game theory. The utility function is designed to optimize the energy efficiency of the system. It is proved that the proposed game model is an exact potential energy game, and the best equilibrium state of the game model is the optimal state of the system energy efficiency. Then a corresponding learning algorithm is proposed, which makes the system achieve the best equilibrium state in the theoretical analysis after a certain step of learning iteration, obtain the optimal stable solution of the energy efficiency of the system, and realize the global optimal energy efficiency of the system. Secondly, aiming at the problem that the wireless sensor node information needs to select the appropriate backbone network access point for energy efficiency optimization in the Internet of things, this paper first establishes the mathematical model of the system level energy optimization of the sensor node freely selecting the access point. Then the game model based on the concept of cooperation and the corresponding utility function are proposed. Through theoretical analysis, it is proved that the optimal access point allocation scheme is the best equilibrium point of the proposed game. According to this algorithm, the system can converge to the optimal equilibrium point with a high probability, that is, the optimal solution of the energy efficiency optimization problem, and realize the global optimization of the energy efficiency of the system.
【学位授予单位】：浙江工商大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.44;TN929.5

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