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

机译：概率QoS措施下的电信带宽中介的模糊随机模型。

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摘要

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 leasing already purchased capacity to end-users. BB's problem becomes harder to deal with when bandwidth requests of end-users, profit and cost margins are not known in advance. The novelty of the proposed work is the development of a mechanism via combining fuzzy and stochastic programming methodologies for solving complex BP selection and bandwidth demand allocation problem in communication networks, based on the fact that information needed for making these decisions is not available prior to leasing capacity. In addition, suggested model aims to maximize BB's decision maker's satisfaction ratio rather than just profit. As a solution strategy, the resulting fuzzy stochastic programming model is transformed into deterministic crisp equivalent form and then solved to optimality. Finally, the numerical experiments show that on the average, proposed approach provides 14.30% more profit and 69.50% more satisfaction ratio compared to deterministic approaches in which randomness and vagueness in the market and infrastructure are ignored.
机译：在本文中，我们建模并解决了不确定的市场和网络基础设施条件下的电信带宽经纪人（BB）的利润最大化问题。 BB可以从一组骨干提供商（BP）或其他BB租用网络容量，以通过将已购买的容量出租给最终用户来获取利润。如果事先不知道最终用户的带宽需求，利润和成本边际，BB的问题将变得更加难以解决。拟议工作的新颖之处在于，通过结合模糊和随机规划方法来开发一种机制来解决通信网络中的复杂BP选择和带宽需求分配问题，该机制基于以下事实：做出这些决定所需的信息在租赁之前不可用。容量。此外，建议的模型旨在最大化BB决策者的满意度，而不仅仅是利润。作为一种解决策略，将所得的模糊随机规划模型转换为确定性的清晰等效形式，然后求解为最优。最后，数值实验表明，相比于忽略了市场和基础设施的随机性和模糊性的确定性方法，所提议的方法平均提供了14.30％的利润和69.50％的满意率。

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