QoS issues in adaptive scheduling in heterogeneous networks with linear pricing scenario

This paper presents an adaptive scheduling and CAC model for the revenue maximization. The algorithm shares limited resources to different traffic flows in a fair way, and at the same time it maximizes the revenue of the service provider. Used algorithm is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic flows, not about call density functions or duration distributions. One possible implementation target to the algorithm could be justify it to work with IEEE 802.11e.