Performance Degradation in Parallel-Server Systems with Shared Resources

Abstract

Parallel server systems are ubiquitous. Multicore CPUs are in practically every personal device from mobile handsets to high-end desktop PCs. At larger scale, data centers consist of a huge number of physical servers often shared by multiple users (for economic reasons). Moreover, the simultaneous users are typically unaware of each other due to reasons that can be technical (cf. security & privacy), practical (coordination layer would add complexity) and business related (usage can be business sensitive information). This results in server-side variability in terms of unpredictable response times. We study means for tackling these challenges. In particular, we consider a model where multiple users (dispatchers) route their jobs to a pool of servers using different (dispatching) policies. The goal is to determine how different policies interact: whether users' decisions support each other, or if some decisions are simply counterproductive. The lack of coordination is shown to increase, e.g., the mean response times, with two common and robust dispatching policies: the static Size-Interval-Task Assignment (SITA) and the dynamic Round-Robin (RR). We refer to this phenomenon as the price of ignorance.