Adaptive clustering reconstruction algorithm of the Internet of Things after coal mine disaster
ZHAO Qing,YANG Wei,HU Qingsong
针对煤矿物联网灾后重构网络中簇头节点易于因能量耗尽或环境破坏而失效导致重构网络不稳定的问题,提出了一种自适应重构的加权分簇组网算法,以优化重构网络分簇过程和提高重构网络的稳定性。首先,在分簇阶段,分析了节点的能量因子、连接度、距离度和节点的失效概率4种可能影响分簇性能的因素。然后,每个节点通过与Sink节点以及邻节点的信息交互可以计算得到自身的一个簇头选举参数,并通过与通信范围内其他节点的簇头选举参数相比,决定自身是否成为簇头节点或簇成员节点。当所有的残存节点都确定自身成为簇头节点或簇成员节点时,则重构网络的分簇过程完成。其次,在网络运行阶段,由Sink节点以一个较小时隙定期发送探测消息,并更新各簇的成员信息列表。分别设置簇头剩余能量函数和链路质量函数,当簇头剩余能量函数和链路质量函数任一的判决函数低于设定的阈值时,Sink节点在网络中宣布该簇头节点死亡消息,并重新启动重构网络新一轮的分簇过程。仿真结果表明,与典型的LEACH和WCA分簇算法相比,采用所提出的自适应重构加权分簇组网算法,可有效降低重构网络总的簇头变化次数,使所形成的簇结构更稳定;保证簇内节点分布较均匀,使得灾后重构网络的总体能耗得到有效降低。当簇头节点剩余能量或链路质量低于阈值门限时自动重新启动网络重构过程,可延长重构网络的生命周期,提高灾后重构网络的稳定性。所提算法为煤矿灾后物联网的重构提供了一种有效的解决方案。
Aiming at the problem that the cluster head node is easy to fail due to energy exhaustion or environmental damage in the reconstruction network of the Internet of Things in coal mine,an adaptive reconstruction weighted cluster network algorithm is proposed to optimize the process of network clustering and improve the stability of the reconstruction network.Firstly,in the clustering stage,the energy factor,connectivity,distance and failure probability of nodes are analyzed.Then,each node can calculate its own cluster head election parameter through information interaction with sink node and neighboring nodes,and determine whether it becomes a cluster head node or a cluster member node by comparing with the cluster head election parameters of other nodes in the communication range.When all the remaining nodes decide to be cluster head nodes or cluster member nodes,the process of reconstructed network clustering is completed.Secondly,in the operating stage,sink node periodically sends the detection message in a small time slot and updates the member information list of each cluster.The cluster head residual energy function and link quality function are built.When either of the above two functions of the cluster head is lower than the set threshold value,sink node announces the death message of the cluster head node in the network,and restarts a new round of clustering process of the reconstructed network.The simulation results show that compared with the typical Leach and WCA clustering algorithms,the proposed adaptive reconstruction weighted clustering algorithm can effectively reduce the total number of cluster head changes of the reconstructed network,make the cluster structure more stable,ensure the distribution of nodes in the cluster is more uniform,so that the overall energy consumption of the post-disaster reconstruction network can be effectively reduced.When the residual energy or link quality of cluster head node is lower than the threshold value,the network reconfiguration process can be restarted automatically,which can prolong the life cycle of the reconstruction network and improve the stability of the reconstruction network after disaster.The proposed algorithm provides an effective solution for the reconstruction of the IoT after the coal mine disaster.
coal mine disasters;Internet of Things (IoT);node failure;self-adaptive reconstruction;clustering network
1 灾后问题描述与网络模型
1.1 问题描述
1.2 网络模型
2 综合度量指标
2.1 节点能量因子
2.2 节点连接度
2.3 节点距离度
2.4 节点失效概率
2.5 综合度量指标
3 自适应重构加权分簇组网算法
3.1 自适应加权分簇过程
3.2 簇头失效重构机制
4 仿真结果及分析
5 结论
主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会