基于超模博弈和最优刚性图的跨层拓扑控制算法

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Jingjing Wang;Jia Gao;Wei Shi;Shefeng Yan;Guangjie Han
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引用次数: 0

摘要

为了减少和平衡水下节点的能量消耗,本文提出了一种基于超模博弈和最优刚性图的水下无线传感器网络(UWSN)跨层拓扑控制算法。首先,本文结合连接系数、覆盖系数、邻居节点干扰、平均剩余能量比等各层参数,设计了一个超模博弈模型,证明了纳什均衡的存在性。在这个阶段,我们可以动态调整节点的发射功率和通信范围。然后,基于成功率和节点能量信息构建链路权重函数,利用最优刚性图原理剔除网络中的冗余链路;该算法可以动态调整网络拓扑结构,提高网络传输质量,有效延长网络寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-Layer Topology Control Algorithm Based on Supermodular Game and Optimal Rigid Graph
To reduce and balance the energy consumption of underwater nodes, this article proposes a cross-layer topology control algorithm for underwater wireless sensor network (UWSN) based on supermodular games and optimal rigid graphs. First, this article combines the parameters of different layers such as connectivity factor, coverage factor, neighbor node interference, and average ratio of residual energy to design a supermodular game model and proves the existence of Nash equilibrium (NE). In this stage, we can adjust the transmitting power and communication range of nodes dynamically. Then, the link weight function is constructed based on success rate and node energy information, and the redundant links in the network are eliminated by using the principle of optimal rigid graph. This algorithm can dynamically adjust the network topology, improve the quality of network transmission, and effectively prolong the network lifetime.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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