Towards Scalable and Expressive Stream Packet Processing

Modern multi-core servers are powerful enough to process multi-gigabit live packet streams on the network data plane. However, in most cases network programmers must build their applications from scratch, by implementing both the interfaces towards the lower hardware level and the proper mechanisms for parallel programming. Data Stream Processing (DaSP) frameworks have recently emerged as promising approaches to overcome the above issues and to let programmers simply focus on the logic of the application to develop. However, DaSP platforms are generally not designed for the networking domain, in terms of both performance and functions. In this paper, we selected the WindFlow DaSP framework and built suitable extensions to attach multiple (accelerated) packet sources of data to it. We then implemented a simple monitoring application on top of WindFlow and carried out stress tests with synthetic and real traffic. The results prove that performance scale linearly with the processing cores so that the application was able to process the whole amount of live data up to nearly 20 Gbps rate.