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In the authors' previous work on distributed backpressure routing for WiFi Mesh Networks (WMN), they showed that backpressure routing when combined with geographic information results in a (quasi-) stateless low-overhead (hence scalable) routing solution. Specifically, the Lyapunov drift-plus-penalty optimization framework allows trading off between routing decisions for maintaining queue backlogs under control (and hence, the network stable) and those that try to get close to the optimal value of an objective performance metric. Such framework offers a non-negative parameter (V) for weighting both components.
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