Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements

In “Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements,” Lei and Jasin consider a fundamental dynamic pricing problem when resources are reusable. In this problem, demand arrives according to a price-sensitive nonstationary rate, requesting a service that uses a combination of different types of resources for a deterministic duration of time. The resources are reusable in the sense that they can be immediately used to serve a new customer on the completion of the previous service. Moreover, different customers may have different service time requirement and may book the service in advance. The objective is to construct a dynamic pricing control that maximizes expected total revenues. They develop real-time heuristic controls based on the solution of the deterministic relaxation of the original stochastic problem and show that the proposed controls are near optimal in the regime of large demand and large resource capacity.

Adaptive Presentation and Scheduling of Media Streams on Parallel Storage Servers

One way to implement adaptive software is to allocate resources dynamically during run-time rather than statically at design time. Design of adaptive software and adaptive execution of processes are key factors that improve versatility of software and decrease maintenance costs. In this chapter we study the development of adaptive software focusing on a design strategy for the implementation of parallel media servers with an adaptable behaviour. This strategy makes the timing properties and the quality of presentation of a set of media streams predictable. The proposed adaptive scheduling approach exploits the performance of parallel environments and seems a promising method that brings the advantages of parallel computation in media servers. The proposed mechanism provides deterministic service for both Constant Bit Rate (CBR) and Variable Bit Rate (VBR) streams. We present an efficient placement strategy for data frames as well as an adaptability strategy that allows appropriate frames to be dropped without sacrificing the ability to present multimedia applications predictably in time.