Computation Against a Neighbour: Addressing Large-Scale Distribution and Adaptivity with Functional Programming and Scala

Recent works in contexts like the Internet of Things (IoT) and large-scaleCyber-Physical Systems (CPS) propose the idea of programming distributedsystems by focussing on their global behaviour across space and time. In thisview, a potentially vast and heterogeneous set of devices is considered as an"aggregate" to be programmed as a whole, while abstracting away the details ofindividual behaviour and exchange of messages, which are expresseddeclaratively. One such a paradigm, known as aggregate programming, builds oncomputational models inspired by field-based coordination. Existing models suchas the field calculus capture interaction with neighbours by a so-called"neighbouring field" (a map from neighbours to values). This requires ad-hocmechanisms to smoothly compose with standard values, thus complicatingprogramming and introducing clutter in aggregate programs, libraries anddomain-specific languages (DSLs). To address this key issue we introduce thenovel notion of "computation against a neighbour", whereby the evaluation ofcertain subexpressions of the aggregate program are affected by recentcorresponding evaluations in neighbours. We capture this notion in theneighbours calculus (NC), a new field calculus variant which is shown tosmoothly support declarative specification of interaction with neighbours, andcorrespondingly facilitate the embedding of field computations as internal DSLsin common general-purpose programming languages -- as exemplified by a Scalaimplementation, called ScaFi. This paper formalises NC, thoroughly compares itwith respect to the classic field calculus, and shows its expressiveness bymeans of a case study in edge computing, developed in ScaFi