LOcAl DEcisions on Replicated States (LOADER) in programmable dataplanes: Programming abstraction and experimental evaluation

摘要

Programmable data planes recently emerged as a prominent innovation in Software Defined Networking (SDN). They provide support for stateful per-packet/per-flow operations over hardware network switches specifically designed for network processing. Unlike early SDN solutions such as OpenFlow, modern stateful data planes permit to keep (and dynamically update) per-flow states local to each switch, thus dramatically improving reactiveness of network applications to different state changes. Still, in stateful data planes, the management of non-local states is assumed to be completely delegated to a centralized controller, thus requiring extra overhead to be accessed.Our LOADER proposal aims at contrasting the apparent dichotomy between local and non-local states. We do so by introducing a new possibility: permit to take localized (in-switch) decisions not only on local states but also on global replicated states, thus providing support for network-wide applications without incurring the drawbacks of classic approaches. To this purpose, (i) we provide high-level programming abstractions devised to define the states and the update logic of a generic network-wide application, and (ii) we detail the underlying low-level state management and replication mechanisms. We then show LOADER's independence of the stateful data plane technology employed, by implementing it over two distinct stateful data planes (P4 switches and OPP - Open Packet Processor - switches), and by experimentally validating both implementations in an emulated testbed using a simple distributed Deny-of-Service (DoS) detection application.