Scheduling and Dynamic Pricing with Service Differentiation

摘要

In this paper we consider an Internet router providing service differentiation like in a DiffServ domain, controlled by a dynamic pricing mechanism. The system is modelled by a multi-class queue and we consider that users choose their class of service by observing the current state of the system. Each user values his service using a utility function and their decision depends on their service valuation. The way of users take their decision depending on the utility function is called a policy. One way to provide service differentiation in a ingress DiffServ router is to employ different scheduling algorithms. We propose in this paper to compare, from a pricing perspective, the t-wo scheduler Strict Priority (SP) and Weighted Fair Queueing (WFQ) used to provide service differentiation in DiffServ. We study an optimal dynamic pricing algorithm for the SP scheduler using a Markov decision framework based on reinforcement learning. Finally we compare the provider revenue with the one obtained in [1] with a WFQ algorithm.