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Integrating Predictable Planning and Unpredictable Dynamics in Network Utility Maximization: An Improved Quota-Based Market Model

Pricing schemes for network utility maximization are playing an increasingly important role for optimal resource allocation within communication networks. Nevertheless, most pricing-based resource allocation mechanisms in the literature are quite complicated and may not be practical to implement in real networks. In this paper, we propose a novel incentive engineering mechanism which incorporates a cumulus point mechanism facilitating the mapping of user's traffic from shorter time scales to relative longer time scale, and at longer time scale, implements a virtual monetary nuglet mechanism derived from classic quota-based predictive scheme. The nuglets are allocated to each user according to agreed traffic contract and are traded between users and service provider for real transmission service. This improved quota-based market model facilitates both prediction of resource allocation for each user and adjustment of admission decision making based on network dynamics. The system model shows the application of proposed mechanism in admission control for a congested access point in wireless network. Through decomposing the original problem into distributed optimization problems separately and solved by service provider locally through adjusting charging rate or individually at the user's side by changing their service requests reasonably, maximization of both user's utility and service provider's revenue are achieved. Evaluation demonstrates that our improved quota-based market model indeed provides a good balance among various perspectives that define the overall performance of a charging scheme