战术互联网中基于信任的k跳复合度量分簇算法

k-hop compound metric clustering algorithm based on trust in tactical Internet

在分析战术互联网特点的基础上,提出了一种基于信任的k跳复合度量分簇算法TBKCM。综合考虑节点行政级别、节点信任度、剩余电池电量、节点相对移动性、节点ID来选举簇首,提高了网络的安全性和稳定性。将一跳簇扩展为k跳,增强了网络的可扩展性。采用按需触发簇维护策略,能够及时有效地维护网络拓扑,同时减少控制开销。仿真实验表明,TBKCM方案产生的簇有适度且统一的簇尺寸,与其他方案相比,具有更长的簇首持续时间,簇结构更加稳定。

Based on the analysis of the characteristics of Tactical Internet （ TI）, this paper presented a trust based k -hop compound metric clustering algorithm （TBKCM）, which used the node＇s administration level, trust level, residual energy, relative mobility, and identity jointly to select cluster heads, thus enhanced the network security and stability. As one hop cluster was extended into k hops, TBKCM improved the scalability of large scale TI significantly. This scheme introduced an on-demand cluster maintenance strategy in order to maintain network topology available and timely, at the same time, to reduce the cost of control. The simulation results show that, clusters created by using TBKCM approach retain modest and more uniform cluster size. The cluster head duration time increased compared with other clustering schemes and thus created much more stable clusters.