Clustering can increase the performance of large-scale mobile ad hoc networks effectively. But the highly dynamic mobile ad hoc networks have some of characteristics

such as high mobility and fast network topology change;applying traditional clustering algorithms will cause the sharp decrease of the performance of the network

frequent updates of cluster topology will cause the instability of cluster structure and the increase of control overhead. For purpose of solving the problems that traditional clustering algorithms cannot fit the highly dynamic large-scale mobile ad hoc networks

BIMAC (Bio-Inspired Mobility-Aware Clustering) algorithm is proposed. This algorithm ameliorates the forage model of physarum polycephalum

which can make it adapt to the domain of mobile ad hoc networks. On account of this algorithm includes the mobility characteristic of the node

we can carry through the cluster formation and maintenance effectively. Experimental results have indicated that the BIMAC algorithm increases average link connection lifetime and average cluster head lifetime compared with other traditional clustering algorithms;BIMAC algorithm can make the cluster structure more stable. This algorithm can increase the adaptive capacity for highly dynamic large-scale mobile ad hoc networks.