  In designing wireless sensor networks, it is important to reduce energy
dissipation and prolong network lifetime. In this paper, a new model with
energy and monitored objects heterogeneity is proposed for heterogeneous
wireless sensor networks. We put forward an energy-efficient prediction
clustering algorithm, which is adaptive to the heterogeneous model. This
algorithm enables the nodes to select the cluster head according to factors
such as energy and communication cost, thus the nodes with higher residual
energy have higher probability to become a cluster head than those with lower
residual energy, so that the network energy can be dissipated uniformly. In
order to reduce energy consumption when broadcasting in clustering phase and
prolong network lifetime, an energy consumption prediction model is established
for regular data acquisition nodes. Simulation results show that compared with
current clustering algorithms, this algorithm can achieve longer sensor network
lifetime, higher energy efficiency and superior network monitoring quality.
