Abstract
The access of multimedia computing in wireless networks is concerned with 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 decisions with an evaluation of link quality instead of a comparison between relative signal strength. The experimental and simulation results show that the number of lost packets is minimized using the proposed algorithm without incurring unnecessary handoffs.
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