Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2018/6421717/figures/6421717.fig.007a.svgz" name="6421717.fig.007a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Hop count</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2018/6421717/figures/6421717.fig.007b.svgz" name="6421717.fig.007b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Remaining energy</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/wcmc/volume-2018/6421717/figures/6421717.fig.007c.svgz" name="6421717.fig.007c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Output weight</td></tr></table>

<div>EW membership function: Hop count, remaining energy, and output weight.</div>

Wireless Communications and Mobile Computing

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Figure 7

Figure 7: Congestion Control and Prediction Schemes Using Fuzzy Logic System with Adaptive Membership Function in Wireless Sensor Networks 