flow-optimized random access for wireless multihop networks
We study a time slotted random access network carrying elastic data traffic. We assume that the link access probabilities can be controlled on time scales comparable to network flow state changes but remain constant on shorter time scales and in particular do not react to slot-level backlogs. Capacity sets of such networks are defined, i.e. the effective link capacities which can be achievedby tuning the transmission probabilities. We revisit the problem of finding the capacity set and give an analytical characterization for the case of a single resource, which was derived already by Kleinrock. For the multihop case we provide a general algorithm to determine the boundary of the capacity set. The main contribution of the paper is to combine the capacity set results with the concept of balanced fairness to analyze the file transfer throughputs in a dynamic setting where a stochastically evolving number of file transfers adapt their rates to share the network resources among each other. Our numerical analysis shows that for light loads and short routes the throughput under flow-optimized random access is close to optimal that of slot-by-slot link scheduling, even though the control time scale required by the random access is much slower. With heavy loads the performance deteriorates.
network capacity analysis flow level performance multihop aloha networks