QoS Evaluation of End-to-End Services in Virtualized Computing Environments

Abstract

Quality of service (QoS) optimization for end-to-end (e2e) services always depends on performance analysis in cloud-based service delivery industry. However, performance analysis of e2e services becomes difficult as the scale and complexity of virtualized computing environments increase. In this paper, the authors present a novel hierarchical stochastic approach to evaluate the QoS of e2e virtualized cloud services using Quasi-Birth Death structures, where jobs arrive according to a stochastic process and request virtual machines (VMs), which are specified in terms of resources, i.e., VM-configuration. To reduce the complexity of performance evaluation, the overall virtualized cloud services are partitioned into three sub-hierarchies. The authors analyze each individual sub-hierarchy using stochastic queueing approach. Thus, the key performance metrics of e2e cloud service QoS, such as acceptance probability and e2e response delay incurred on user requests, are obtained.