The access of multimedia computing in wireless networks is concerned about the efficiency of handoff because of the irretrievable property of real-time data delivery. To lessen throughput degradation leading to media computing disruption perceived by users, this paper presents a link quality based handoff algorithm. Neural networks are used to learn the correlation between link quality estimator and the corresponding context metric indictors. Based on a pre-processed learning of link quality profile, neural networks make efficient handoff decision with the evaluation of link quality instead of the comparison between relative signal strength. The experiment and simulation results show that the number of lost packets is minimized using the proposed algorithm without incurring unnecessary handoffs.