动态物联网应用环境中无线传感器网络拓扑加权演化机制及自组织节能策略研究

Internet of Things (IoT) is designed to provide convenient services for users so that they can obtain information and control equipments no matter “anywhere, anytime, anything, anyone”. Being responsible for information sensing and end-network transmission, wireless sensor networks (WSN) is as a key supporting technology of IoT. WSN consist of massive wireless sensor nodes, all of which have limited energy and communication ability. ..Researches on weighted topology evolving mechanism of WSN and its self-organized energy-saving strategy in dynamic IoT application environment with big data will be done in this project, which is based on inter-disciplinary theories (such as intelligent control), supported the features of activity of topology evolving of WSN and self-organization of energy-saving, and tested by example cases of energy- consumption mobile control of WSN (such as planting of warm house, coal mining under the deep well). ..The main contents of this research (which are associated) are as follows...i)Propose an improved BBV model based on flow load of WSN and weighted topology evolving mechanism of WSN based on idea of local-world and uneven-clustering, which is the basis of energy-saving strategy..ii)Propose method of avoiding transmission data collision based on perceived data reliability and spatial correlation, which can decrease the energy-consumption..iii)Propose method of energy-consumption self-adaptive control of data transfer based on network load dynamic mutations, which can solve the problem of unfairness of the energy-consumption and delay..iv)Propose an energy-balanced routing strategy FAF-EBR based on forward- aware factor,which can prolong the function lifetime of WSN and improve the self-organization of energy-saving. .v)Supply the function of energy-consumption mobile control of WSN by our implemented mobile computing platform...The goal of this project is to improve the intelligence level of energy-saving and topology structure evolving of WSN, and promote the more development of IoT.

本项目以带有大数据的动态物联网应用为背景，以支持无线传感器网络(WSN)拓扑演化的主动性及节能的自组织性为特征，以智能控制等理论为基础，以大棚种植和井下煤矿中WSN能耗移动监控为应用案例，研究动态物联网应用环境中WSN拓扑加权演化机制及自组织节能策略。主要研究内容为相互关联的如下4个方面：1)提出基于网络流量负载的改进BBV模型和基于局域世界与不均匀成簇思想的网络拓扑加权演化机制，为节能降耗提供前提条件。2)提出基于感知数据可靠性和空间相关性的数据碰撞冲突退避方法，以降低能耗。3)提出适应网络流量动态变化的数据传送能耗自适应控制方法，解决网络能耗与延时之间的不协调问题。4)提出基于前向感知因子的能量均衡的节能路由策略，延长网络工作寿命，提高节能的自组织性。同时，利用我们研发的移动计算平台，提供能耗移动监控功能。.本项目旨在提高WSN拓扑结构演化及自组织节能的智能水平，促进物联网技术的发展。

本项目以带有大数据的动态物联网应用为背景，以支持无线传感器网络(WSN)拓扑演化的主动性及节能的自组织性为特征，以智能控制等理论为基础，以大棚种植和井下煤矿中WSN能耗移动监控为应用案例，研究了动态物联网应用环境中WSN拓扑加权演化机制及自组织节能策略。主要研究内容为相互关联的如下4个方面：1)提出了基于网络流量负载的改进BBV模型和基于局域世界与不均匀成簇思想的网络拓扑加权演化机制，为节能降耗提供前提条件。2)提出了基于感知数据可靠性和空间相关性的数据碰撞冲突退避方法，以降低能耗。3)提出了适应网络流量动态变化的数据传送能耗自适应控制方法，解决了网络能耗与延时之间的不协调问题。4)提出了基于前向感知因子的能量均衡的节能路由策略，延长了网络工作寿命，提高了节能的自组织性。同时，利用我们研发的移动计算平台，提供了能耗移动监控功能。.本项目的研究成果提高了WSN拓扑结构演化及自组织节能的智能水平，促进了物联网技术的发展。