A fuzzy stochastic model for telecommunications bandwidth brokers under probabilistic QoS measures

In this paper, we model and solve profit maximization problem of a telecommunications Bandwidth Broker (BB) under uncertain market and network infrastructure conditions. The BB may lease network capacity from a set of Backbone Providers (BPs) or from other BBs in order to gain profit by selling already purchased capacity to end-users. However, BB’s problem becomes harder to deal with when bandwidth requests of end-users, profit and cost margins are not known in advance. The fuzzy set theory and stochastic programming techniques are employed in this article due to the presence of vagueness and randomness in mentioned parameters. In addition, this study not only considers uncertainties in market but also takes into account uncertainties arising because of infrastructure conditions of networks. Therefore not only cost but also Quality of Service (QoS) offered by BPs has to be investigated by BB before acquisition of capacity. The proposed novel model is formulated in such a way that it simultaneously considers the randomness in demands and prices then selects BPs and determines the allocation scheme of end-users’ bandwidth requests into purchased capacity. Finally, the efficiency and superiority of methodology compared to deterministic approach are demonstrated by running several randomly generated test instances.