| 摘要: |
| 针对UWSNs由网络拓扑控制不稳定、频繁变化引起网络的能耗不均衡、网络生存周期短等问题，从分析传感器节点受水下不确定性因素对UWSNs的拓扑结构演化入手，构建分布式水下传感器节点状态变量描述模型，归纳出节点之间和节点与环境之间多目标交互、协同、决策的UWSNs拓扑控制优化问题，将多目标优化问题映射成博弈论优化问题，再利用势博弈与Log-linear分布式学习规则实现博弈中节点策略行为的更新过程，采用非齐次马尔可夫链理论证明网络拓扑控制目标函数的优化问题收敛到最大化势博弈函数的解，从而达到保持网络均衡、延长网络生存周期的目的. |
| 关键词: 网络拓扑控制 势博弈 时变Log-linear模型 马尔可夫链 生存周期 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金（61571150，61872204）；黑龙江省自然科学基金（LH2019F037）；研究生创新科研项目（YJSCX2018-ZD09） |
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| Potential Game and Time-varying Log Linear Distributed Topology Control Algorithm |
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WEI Lian-Suo, HAN Jian, CHEN Qi-Qi, HU Xian-Cheng
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School of Computer and Control Engineering, Qiqihar University, Qiqihar 161006, China
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| Abstract: |
| Aiming at the problems of UWSNs, such as unstable network topology control, unbalanced energy consumption caused by frequent changes and short network lifetime, this paper starts with the analysis of the evolution of topology caused by underwater uncertainties of sensor nodes, builds a state variable description model of distributed underwater sensor nodes, and concludes the multi-objective interaction and collaboration between nodes and environment. Topology control optimization problem for decision-making is mapped into game theory optimization problem. Then, potential game and Log-linear distributed learning rules are used to update the strategy behavior of nodes in the game. The non-homogeneous Markov chain theory is used to prove that the optimization problem of network topology control objective function converges to the solution of maximizing potential game function, so as to achieve guaranteeing. The purpose of maintaining network balance and prolonging network lifetime is to achieve the goal of maintaining network balance. |
| Key words: network topology control potential game time-varying Log-linear model markov chain lifetime |
