基于链接率的AdHoc自适应按需加权分簇算法

AdHoc网络通过分簇算法来实现网络分层，以支持高效的资源管理和路由策略。稳定的分簇算法可以减少网络的计算和通信开销。为了提高分簇算法的稳定性，文中提出了一种基于链接率的自适应按需加权分簇算法（AOWLR）。该算法将节点的运动轨迹抽象为直线形和圆弧形两种，并引入邻居节点的平均链接率预测值作为衡量簇稳定性的一个重要标准。NS2仿真结果证明，同AOW相比，AOWLR算法的负载平衡因子较高，连通统治集（CDS）更新频率和节点充当簇头的公平性指数（HFI）较低。

An Adaptive On-demand Weighting Clustering Algorithm Based on Linking Rate in Ad Hoc Networks

Ad Hoc networks use clustering algorithm to achieve hierarchical network to support effective resource management and routing strategies. A stable clustering algorithm can reduce the network overhead in calculation and communication. In order to improve the stabil- ity of clustering algorithm, a novel adaptive on-demand weighting clustering algorithm is proposed which is based on the linking rate. The node trajectories are abstracted to arcs and lines. The forecast of the average linking rate of neighboring nodes is used as the standard to measure the cluster＇ s stability. Simulation results show that the AOWLR has higher loading balance factor, lower updating frequency of cluster domination set （CDS） and lower head fairness index （HFI） compared with the AOW.