Modeling Traffic Workloads in Data-center Network Simulation Tools

Abstract

POSTER PAPER Data-centers are commonly used by most important cloud providers worldwide in order to provide storage and computing resources, and, based on these resources, advanced IT services and applications. With the expected explosion of data in the next few years, Data-centers will require new architectures to cope with the new requirements of applications and users. One of the crucial subsystems within the Data-center architecture that must evolve accordingly to the new requirements is the interconnection network or Data-center network (DCN). The DCN performance (basically, high communication bandwidth and low latency) must be guaranteed, otherwise the DCN becoming the system bottleneck. There are several key issues that DCN designers must make decisions on, such as the network topology, routing algorithm, congestion management, etc. An important aspect that impacts on the DCN design are the network communication patterns generated by applications and services. In that sense, an accurate modeling of these traffic workloads would help network designers to make better decisions. In this paper, we present an analysis of the few available studies on traffic modeling for DCNs, in order to gather a set of parameters that define the behaviour of common traffic workloads. Based on these parameters, we have implemented a synthetic DCN traffic generator, which has been included in our simulation framework in order to feed the network with the inferred traffic workloads. We have conducted extensive simulations to test the impact of the parameter variation on the network performance. From the obtained results, we can conclude that the destination distribution is crucial for the network performance. Higher oversubscription of destinations generates incast scenarios that lead to congestion situations and head-of-line blocking, affecting other flows that do not contribute to the incast situation and so spoiling the network performance.