A self-maintenance clustering algorithm based on decision model for space information networks

Space information networks, which have become a popular research focus, are a new type of self-organizing networks. With fully considering characteristics distinguishing space information networks from common self-organizing networks such as terrestrial ad hoc networks and wireless sensor networks, the proposed clustering algorithm introduces a decision model based on analytic hierarchy process (AHP) to select cluster heads, and then forms non-overlapping k-hop clusters. The dynamical self-maintenance mechanisms take node mobility and cluster equalization into account. Besides of cluster merger/partition disposal, reaffiliation management and adaptive adjustment of information update period, mobile agents are used to migrate and duplicate functions of cluster heads in a recruiting way. Simulation results show that our clustering algorithm improves network scalability and is suitable for use in space information networks.