Scheduling time-sensitive multi-tier services with probabilistic performance guarantee

Web applications grow tremendously in both scale and scope, the application patterns turn to be more and more sophisticated. It is important but challenging for service providers to lower the operational costs without degrading user experiences, especially in the case where a service provider's profit is closely related to the user experience (e.g. response time.) In this paper, we study the problem of efficiently scheduling multi-tier time sensitive applications on distributed computing platforms with respect to the user's Quality of Service (QoS) requirements. The efficiency refers to the QoS satisfaction with low average response times. The service provider must ensures that service requests be served successfully before end-to-end deadlines with certain probabilities. To solve this problem, we propose an approach to judiciously assign a deadline for each service tier. An application request is dropped if any one of its services misses its deadline. Our simulation results demonstrate that our approach can statistically guarantee the required QoS more efficiently than the other widely applied methods (e.g. acceptance control, first-come-first-serve, deterministic sub deadline assignment, etc.) irrespective of whether the resources are shared or not by multiple different applications.