Stochastic capacity acquisition and allocation model for bandwidth brokers under fuzzy volume based pricing scheme

In this paper, bandwidth acquisition and allocation problem of a telecommunications Bandwidth Broker (BB) is analyzed under uncertain end-user capacity requests and pay-per-byte (volume) based pricing policy. Furthermore, related objective function coecients such as revenue and costs are modeled as fuzzy numbers in order to cope with vague market conditions. By integrating fuzzy mathematical programming and two-stage stochastic programming techniques, deterministic equivalent of single objective prot maximization problem of BB is obtained solved to optimality. In addition, infrastructure related performance measures such as delay and jitter amounts in the network are modeled via stochastic parameters that obey some known probability distributions. Two performance statistics namely fuzzy EVPI and fuzzy VSS are dened to demonstrate the eciency of proposed methodology compared to deterministic approach. In addition, several secondary performance measures such as expected capacity utilization, expected demand fulfillment ratio and capacity loss are calculated under dierent problem settings. In conclusion, numerical experiments showed that fuzzy stochastic method provides more prot depending upon problem size in compression with deterministic strategy