Abstract
In wireless sensor networks, traditional link selection algorithm needs lots of data packages as testing samples, but the nodes of WSN are battery-powered, so the energy is extremely limited. To overcome this shortcoming, the aim of this paper is to propose three new link selection algorithms based the concept of Bayesian approach. Simulation results demonstrate that the three algorithms based on Bayesian approach have a higher success rate than empirical-algorithm by about 10 percent in selecting the highest quality link with the case of small samples. Among them, BSLA-EB has a good adaptability and it can get better experimental results.
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