混杂多传感网协调通信层次结构建模与多级优化方法

To solve the uncertainty and diversity of network architecture and application objects over internet of things, in this object, we introduce the technologies of sensing, network communication, article intelligence, management theory. And for practical engineering applications, we focus on the research of coordination of multi-sensor networks communication technology, which improves the network service quality and support the service differentiation. Since the diversity of hybird sensor networks and different priorities of various data flows, a hierarchical model is proposed based on the theory of multi color set and a service differentiation model based on bio-inspired competitive model. Then we take the coupling scheme of resources, services and decision-making into consideration, adopt competitive and coordination mechanism to allocate and schedule all system resources rationally, a global intelligent optimization algorithm is proposed to realize the optimization of whole network system. In addition, with the research of the technology of network coding of hybrid network topology, we propose adaptive high-performance coding strategy, which significantly improve the network throughput and reliability, and optimize the transmission performance. Finally, we focus on the practical method according to the theoretical results, a novel method of remote monitoring and control is proposed, and the system also be used in accidents surveillance and prevention, which promotes the depth of theoretical study. The object will provide theoretic basis on the application of hybrid multiple sensor networks, and has important theoretical significance and practical value.

针对在物联网中网络结构和应用对象的不确定性和多样性，利用传感技术、网络通信技术、现代人工智能技术和管理学理论，面向实际工程应用，重点深入研究混杂多传感网的协调通信技术，提高网络服务质量和数据流区分服务。研究混杂多传感网环境下的网络结构多元化及数据流优先级差异，建立基于多色集合理论的网络层次结构模型和基于仿生竞争的服务层次结构模型。研究网络资源、服务和决策的耦合机理，采用竞争和协作机制合理分配与协同调度各种物理、通信与计算资源，提出全局智能优化算法，实现混杂多传感网系统的整体优化。研究混杂无线传感网的网络编码技术，提出适应不同网络环境下的高性能编码策略，提高网络的吞吐率和可靠性，优化网络传输性能。将网络理论成果应用于远程监控、事故监视与预防中，促进理论研究的深入。本课题的研究成果将为应用于实际的混杂多传感网系统提供理论基础，具有重要的理论意义和工程应用价值。

物联网是国家经济技术发展的战略之一，加强物联网的网间跨网能力、提高资源利用率、实现物联网稳定长效运行，是多传感网信息传输的核心研究内容，对多传感网在安防、电力、交通、医疗、环保等领域具有重要意义。本课题针对物联网中的网络结构和应用对象的不确定性和多样性，首先针对传统无线传感器网络中节点电池储能的局限性，提出了一种由超级电容和电池组成的混合储能结构，并基于高斯双工信道建立理论模型，以吞吐量最大化为目标提出了单跳和两跳二维无线能量传输算法；针对传感器数据采集问题，研究非固定周期采样频率对网络的影响，设计了面向节能和容错的拓扑结构优化算法；基于时间序列预测模型，综合考虑节点的时间相关性和空间相关性，结合人工智能算法，设计网络结构自适应控制和节点采用自适应控制算法；针对无线多播重传中网络编码的引入带来编码方法、编码策略和编码时机的问题，基于联合优化、中继协作等思想，对无线多播中基于网络编码的高效重传方法进行设计，保持较低算法复杂度下，找到丢失分组的最优网络编码组合，通过最大化每次重传的增益来减少重传次数或最大化系统平均重传增益。最后，将实际的理论研究应用到实际的工程中来，并设计了一套城市内涝监测预警信息系统。本课题的研究成果将为应用于实际的混杂多传感网系系统提供理论基础，具有重要的理论意义和工程应用价值。

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