Asymptotic dimensioning of stochastic service systems

Abstract

Stochastic service systems describe situations in which customers compete for service from scarce resources. Think of check-in lines at airports, waiting rooms in hospitals or queues in supermarkets, where the scarce resource is human manpower. Next to these traditional settings, resource sharing is also important in large-scale service systems such as the internet, wireless networks and cloud computing facilities. In these virtual environments, geographical conditions do not restrict the system size, paving the way for the emergence of large-scale resource sharing networks. This thesis investigates how to design large-scale systems in order to achieve the dual goal of operational efficiency and quality-of-service, by which we mean that the system is highly occupied and hence efficiently utilizes the expensive resources, while at the same time, the level of service, experienced by customers, remains high.

PhD thesis

References in corpus (3)

• Validity of heavy traffic steady-state approximations in generalized Jackson Networks
• Scheduling a multi class queue with many exponential servers: asymptotic optimality in heavy traffic
• On Lerch's transcendent and the Gaussian random walk