Attribute-based memory updates with priorities for collective adaptive systems

Event-driven programming provides a natural fit for the reactive nature of pervasive systems like the Internet of Things (IoT) and Collective Adaptive Systems (CASs). Attribute-based memory Updates (AbU) is a calculus based on Event-Condition-Action (ECA) rules, well-suited for modeling such decentralized systems. This paper introduces a novel extension of AbU by incorporating ECA rule priorities. We show how this extension facilitates the natural expression of prioritized behaviors and enables the implementation of distributed data structures like Conflict-free Replicated Data Types (CRDTs). Furthermore, by leveraging the local invariants of AbU nodes and priorities we address the problem of enforcing global invariants in order to enhance the reliability and predictability of CASs. This is achieved through a syntactic transformation that projects global invariants into local ones and introduces high-priority synchronization rules, so that system-level properties can be guaranteed without relying on a central authority.