![](bg9.png)
Nash equilibrium our GETOA algorithm approached
to is Lyapunov stable.
The demonstration of our approach consisted of a
network of 15 nodes. We analysed the two blue nodes
that exist further down the network to check their be-
havior under our GETOA algorithm. We found that
one of the nodes increases its utility, while slightly
decreases its ETX value; thus exhibiting better end-
to-end reception. The other node, has to decrease its
utility function, since it was suffering from interfer-
ence. Both nodes converged to transmission power
15.2mA, out of the three available transmission power
levels.
Our future work includes the packet transmission
delay as a constraint to our utility function. This will
give us interesting results on the utility function. Fur-
thermore, we aim to compare our approach with a
log-linear learning algorithm (Monderer and Shapley,
1996) to investigate the differences in performance
and convergence.
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