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The development of programmable switches such as the Intel Tofino has allowed network designers to implement a wide range of new in-network applications and network control logic. However, current switch programming languages, like P4, operate at a very low level of abstraction. This paper introduces SwitchLog, a new experimental logic programming language designed to lift the level of abstraction at which network programmers operate, while remaining amenable to efficient implementation on programmable switches. SwitchLog is inspired by previous distributed logic programming languages such as NDLog, in which programmers declare a series of facts, each located at a particular switch in the network. Logic programming rules that operate on facts at different locations implicitly generate network communication, and are updated incrementally, as packets pass through a switch. In order to ensure these updates can be implemented efficiently on switch hardware, SwitchLog imposes several restrictions on the way programmers can craft their rules. We demonstrate that SwitchLog can be used to express a variety of networking applications in a mere handful of lines of code. 

The P4 language and programmable switch hardware, like the Intel Tofino, have made it possible for network engineers to write new programs that customize operation of computer networks, thereby improving performance, fault-tolerance, energy use, and security. Unfortunately,possibledoes not meaneasy—there are many implicit constraints that programmers must obey if they wish their programs to compile to specialized networking hardware. In particular, all computations on the same switch must access data structures in a consistent order, or it will not be possible to lay that data out along the switch’s packet-processing pipeline. In this paper, we define Lucid 2.0, a new language and type system that guarantees programs access data in a consistent order and hence arepipeline-safe. Lucid 2.0 builds on top of the original Lucid language, which is also pipeline-safe, but lacks the features needed for modular construction of data structure libraries. Hence, Lucid 2.0 adds (1) polymorphism and ordering constraints for code reuse; (2) abstract, hierarchical pipeline locations and data types to support information hiding; (3) compile-time constructors, vectors and loops to allow for construction of flexible data structures; and (4) type inference to lessen the burden of program annotations. We develop the meta-theory of Lucid 2.0, prove soundness, and show how to encode constraint checking as an SMT problem. We demonstrate the utility of Lucid 2.0 by developing a suite of useful networking libraries and applications that exploit our new language features, including Bloom filters, sketches, cuckoo hash tables, distributed firewalls, DNS reflection defenses, network address translators (NATs) and a probabilistic traffic monitoring service.