拥塞控制被广泛用于感知系统传输质量优化，本项目研究拥塞控制算法对无线感知系统中传输质量的多维影响关系，建立基于多维度的网络拥塞与传输质量关系模型，设计基于传输质量的自适应拥塞控制策略；建立感知过程中的传输质量综合衡量体系，通过马尔科夫预测与小参数优化理论计算，结合节点本地信息，估算并建立当拥塞动态产生时节点信息与传输质量的实时影响模型；利用排队论分析关系模型，引入数据压缩与分包的数据优化式拥塞规避算法，研究数据优化在感知周期内对传输质量的影响关系；研究数据转移矩阵与网络负载均衡的关系，结合节点服务队列模型，建立贯穿网络完整生命周期的网络负载特征模型，分析拥塞演化与迁移规律；在数据优化式拥塞规避算法的基础上设计自适应拥塞控制策略，根据节点本地信息与数据转发矩阵动态设定数据优化、路由调度策略，对延迟敏感无线感知系统的发展具有理论价值与实用意义。

Congestion control is widely used in optimization of transmission quality in Wireless Sensing system. This research mainly focus on the multi-dimensional relationship between the congestion control algorithm and the transmission quality in wireless sensing system, establish a multidimensional relational model between network congestion and transmission quality, design an adaptive congestion control strategy based on transmission quality. With the methods of Markov-chain prediction and small parameter optimization theory, we build an integrated measurement system of transmission quality throughout the entire data collection. With this measurement system, we design a model of real time effect to transmission quality by local information when congestion is dynamically generated. After it, the effect to transmission quality of congestion control algorithm will be got when data optimization is employed in each node. Then combined with the algorithm of data optimization, We design a transmission quality based congestion dynamic control strategy in Delay Sensitive Wireless Sensing system, which can dynamic adjust the parameters of date optimization and routing strategy. This project establish a comprehensive feature model of transmission quality and network congestion evolution, design an adaptive congestion control strategy to avoid network congestion and enhance data real-time ability, which has great theoretical value and practical significance to the development of delay sensitive wireless sensing system.