基于WMSN节点定位的拥塞控制算法研究

发布时间：2018-04-08 12:46

本文选题：WMSN节点定位　切入点：拥塞控制　出处：《浙江理工大学》2017年硕士论文

【摘要】：拥塞控制技术(Congestion Control Technology)是针对网络拥塞问题而提出的有效解决方案。在计算机科学、控制理论、运筹学等学科的交叉领域,拥塞控制成为增强系统整体性能的重要方式,同时是多学科技术融合领域的重要研究方向。资源受限是网络拥塞形成的直接原因,但足够多的节点资源仍无法完全避免网络拥塞现象的产生。因此从整体布局上把握系统结构对于完善网络功能和优化资源分配具有指导性意义。目前拥塞控制方案通常采用确定性处理方式,预案功能较弱,在实际应用中存在着多种局限性。本文基于无线多媒体传感器网络(Wireless Multimedia Sensor Network,WMSN)的节点定位系统,通过系统资源管理构建了不确定情况下面向WMSN节点多目标定位的拥塞控制优化模型并对关键算法进行详细研究。首先,结构稳定性是WMSN节点定位系统运行畅通的决定性因素,也是系统运行可靠性和可扩展性的必要条件。为了最大化利用网络资源,本文构建以能耗均衡理论为支撑的混合式节点重部署策略,并在此基础上进一步拓展到三维空间。监测区域内节点具有微距感应,能够智能化检测网络环境、筛选网络拓扑结构确保信息高效传输。然后,定位高效性直接决定了传感器网络运行效率。针对现有网络在拥塞预测方面存在的不足,本文对粗糙集理论和灰关联理论的融合技术进行了重点研究,提出拥塞预估状态下的多目标定位优先级的判定规则。同时引入模糊定位策略以降低不确定因素在定位过程中对拥塞控制的干扰。将二维定位策略拓展到三维定位,大幅降低系统复杂度和网络拥塞概率。其次,多节点信息传输的可靠性是WMSN节点定位系统拥塞控制评估的关键。本文依据非合作博弈论和经济高效的定价模型对多个节点的信息传输策略进行优化。紧急传输较普通传输优先进入动态缓冲机制进行关键链识别。系统根据熵值的变化对信息传输量进行实时监控和智能评估。动态缓冲区的设置及传输计划自适应调节可有效降低网络传输过程中拥塞发生的概率。最后,通过蒙特卡洛方法对WMSN节点定位拥塞控制优化设计算法进行多次仿真实验。实验数据表明系统优化算法能有效提高系统整体性能实现网络拥塞智能控制。
[Abstract]:Congestion control Control technology is an effective solution to network congestion problem.Congestion control has become an important way to enhance the overall performance of the system in the intersecting fields of computer science, control theory, operational research and so on. At the same time, congestion control has become an important research direction in the field of multi-disciplinary technology convergence.Resource limitation is the direct cause of network congestion, but enough node resources can not completely avoid the phenomenon of network congestion.Therefore, grasping the system structure from the overall layout is instructive to improve the network function and optimize the resource allocation.At present, congestion control schemes usually adopt deterministic processing, and the function of pre-plan is weak, which has many limitations in practical application.In this paper, based on the node location system of Wireless Multimedia Sensor Network (WMSN) in wireless multimedia sensor networks, a congestion control optimization model for multi-objective localization of WMSN nodes is constructed through system resource management, and the key algorithms are studied in detail.Firstly, structural stability is the decisive factor for the running of WMSN node positioning system, and it is also a necessary condition for the reliability and expansibility of the system.In order to maximize the use of network resources, this paper constructs a hybrid node redeployment strategy based on energy balance theory, and further extends to three-dimensional space.The nodes in the monitoring area can detect the network environment intelligently and screen the network topology to ensure the efficient transmission of information.Then, the efficiency of the sensor network is directly determined by the location efficiency.Aiming at the deficiency of congestion prediction in existing networks, this paper focuses on the fusion technology of rough set theory and grey correlation theory, and puts forward the decision rules of multi-objective location priority in congestion prediction state.At the same time, fuzzy location strategy is introduced to reduce the interference of uncertain factors in congestion control.In order to reduce system complexity and network congestion probability, 2D localization strategy is extended to 3D location.Secondly, the reliability of multi-node information transmission is the key of congestion control evaluation of WMSN node location system.Based on the non-cooperative game theory and the economic and efficient pricing model, this paper optimizes the information transmission strategy of multiple nodes.The emergency transmission takes precedence over the ordinary transmission to enter the dynamic buffer mechanism to identify the key chain.According to the change of entropy, the system monitors and assesses the amount of information transmission in real time.The setting of dynamic buffer and adaptive adjustment of transmission plan can effectively reduce the probability of congestion in network transmission.Finally, the Monte Carlo method is used to simulate the optimal design algorithm of WMSN node location congestion control.Experimental data show that the system optimization algorithm can effectively improve the overall performance of the system to achieve intelligent network congestion control.
【学位授予单位】：浙江理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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