QoS-oriented wireless routing for smart meter data collection: Stochastic learning on graph

To ensure resilient and reliable meter data collection that is essential for the smart grid operation, we propose a QoS-oriented wireless routing scheme. Specifically tailored for the heterogeneity of the meter data traffic in the smart grid, we first design a novel utility function that not only jointly accounts for system throughput and transmission latency, but also allows for flexible tradeoff between the two with a strict transmission latency constraint, as desired by various smart meter applications. Then, we model the interactions among smart meter data concentrators as a mixed-strategy network formation game. To avoid potential information exchange which is not always practical in meter data collection scenario, a stochastic reinforcement learning algorithm with only private and incomplete information is proposed to solve the network formation problem. Such a problem formulation, together with our proposed stochastic learning algorithm on graph, results in a steady probabilistic route. Both contributions are novel and unique in comparison with existing work on this topic. Another distinct feature of our approach is its capability of effectively maintaining the QoS of smart meter data collection, even when the network is under fault or attack, as verified by simulations.