A fair allocation of utility (application-layer performance) is essential in providing QoS (Quality of Service) guarantee.
References [76, 77] have used this technique in solving allocation or utility maximisation problems in CRN.
However, we are unaware of any research literature on power allocation when utility is a function of the average bit rate over a period of time.
In the following, we will substitute the power prices with their inverse to ease the analysis with regard to the power allocation and utility.
Over the last 20 years, several theoretical [3, 5, 11, 13 16] and practical [2, 6, 12, 17] works have been developed to understand and solve the problems of power allocation and utility maximization for cellular, multihop, peer-to-peer, and digital subscriber line (DSL) networks.
Besides, the selection and allocation of utilities, distribution of steam, and potential power generation can also be determined.
In this case the allocation of utilities among players is irrelevant to him.
For example, some of the allocations to utilities are granted with the expectation that they will be auctioned off and the proceeds will be used to fund renewable energy development.
Such knowledge removes (for the time being) the challenge of consideration of how current resource allocation affects future utility.
A number of studies have attempted to develop a practical economic model for tiered service, but failed to effectively capture the complex interaction between pricing, resource allocation, and user utility in tiered service.
