A Functional Complexity Framework for Dynamic Resource Allocation in VANETs
In this work we present a complex systems science analysis of the Self Organized Time Division Multiple Access (SOTDMA) algorithm. We translate the interaction among member nodes into a functional topology graph in order to measure the effect of each individual node’s adaptability on the global performance. The functional complexity metric corresponding to the functional topology is shown to have substantial correlation with important Key Performance Indicators (KPIs), namely probability of collision and probability of correct packet detection. We further use the functional complexity metric to analyze the trade-off between the two aforementioned KPIs in terms of system parameters. We finally show that the results obtained using this approach satisfy the predefined KPI constraints imposed on the algorithm and thus is successful in capturing the system behavior.