No abstract

With the advancement of multicore servers, there is a new trend of moving network functions to software servers. Measurement is critical to most network functions as it not only helps the operators understand the network usage and detect anomalies, but also produces feedback to the control loop in management tasks such as load balancing and traffic engineering. Traditional researches on measurement algorithms mainly focus on reducing the memory usage leveraging the fact that measurement can sustain bounded inaccuracy. In this study, we re-evaluate these algorithms on software servers in order to understand their tradeoffs of accuracy and performance. We observe that simple hash tables work better than more advanced measurement algorithms for a variety of measurement scenarios. This is because with better cache design in modern servers and the skewness in the access patterns of measurement tasks, the memory usage of measurement tasks is largely irrelevant to the packet processing performance.

No abstract

Network function virtualization promises a path to rapid innovation in networks. However, due to the complexity of developing these functions, innovations have been slow. Designing a network function is a daunting task that requires combining packet processing optimizations with the network function logic. It is not possible to ignore packet processing optimizations either: an optimized pipeline can have three times better performance than an unoptimized pipeline in our experiments. In this paper, we introduce NFMorph, a framework wherein the algorithms (i.e., the network function logic) are decoupled from the packet processing optimizations. Developers would specify the packet processing algorithms in a high-level language. The runtime then identifies the best set of optimizations on the algorithms. This is done based on the domain knowledge that operators provide as input to NF-Morph as well as optimization templates we have developed for common NF primitives. NFMorph can also just-in-time reoptimize based on workloads and environment constraints.