物联网结合各种主干传输很适合远程实时监测，但随着监测范围的不断扩大与应用的不断普及，监测系统中断所造成的代价和影响与日俱增。系统的拓扑可靠性是保障远程监测系统可靠的一个重要方面，以三江源大面积物联网远程生态监测中需要设立监测区域的实际需求为背景，提出了一种基于均匀分簇的可扩展的模块化传感器节点部署方法，对设置传感器的拓扑结构层数、监测面积和监测节点数等参数的相互关系给出了量化的计算公式，针对不稳定的信息传输环境给出了保障监测区域和远程主干拓扑可靠性的有效机制及量化分析方法，在此基础上，重点给出了关键传输节点(簇头节点和协调器)拓扑可靠性的动态优化策略。理论分析和仿真结果表明：该机制具有数据融合均匀、有效节能和灵活可扩展等特点，对提高物联网远程监测的可靠性有显著效果；同时，所得出的相关理论对诸如农业、牧业和林业等相关行业的偏远大面积物联网远程实时监测的拓扑可靠性保障具有重要的理论和实际应用参考价值。%Internet of things (IoT), combined with various backbone transmission, is very suitable for remote real-time monitoring. However, along with the expansion of monitoring scope and popularization of the application, the cost and impact caused by system interruption is increasing rapidly. Reliability of system topology is very important in guaranteeing the reliability of remote monitoring system. Taking the actual demand of setting up monitoring region for the IoT-based Three-River Source region remote monitoring as background, this paper proposes a scalable uniform clustering based modular sensor deployment method, and gives calculation formula for the relationship between the layer number of topological architecture, the monitored area and the sensor number. To address the unstable information transmission environment, this paper presents an effective mechanism and quantitative analysis method to guarantee the reliability of monitored region and remote backbone topology. This method highlights a dynamic optimization strategy to the topological reliability of those key transmission nodes. Theoretical analysis and simulation results show that this method is placed on traits such as even data fusion, effective energy saving and extensibility and is remarkable in improving the reliability of IoT-based remote monitoring. At the same time, theories from this paper have important theoretical and actual application reference value in guaranteeing topological reliability of IoT-based remote real-time monitoring of large region, such as agriculture, animal husbandry and forestry related industries.
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