ZodiacEdge: a Datalog Engine With Incremental Rule Set Maintenance
In this paper, we tackle the incremental maintenance of Datalog inference materialisation when the rule set can be updated. This is particularly relevant in the context of the Internet of Things and Edge computing where smart devices may need to reason over newly acquired knowledge represented as Datalog rules. Our solution is based on an adaptation of a stratification strategy applied to a dependency hypergraph whose nodes correspond to rule sets in a Datalog program. Our implementation supports recursive rules containing both negation and aggregation. We demonstrate the effectiveness of our system on real and synthetic data.
Code (0)
등록된 구현이 없습니다.
Tasks
Edge-computingNegationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A Differential Datalog Interpreter
The core reasoning task for datalog engines is materialization, the evaluation of a datalog program over a database alongside its physical incorporation into the database itself. The de-facto method of computing it, is t…
Modular Materialisation of Datalog Programs
The semina\"ive algorithm can materialise all consequences of arbitrary datalog rules, and it also forms the basis for incremental algorithms that update a materialisation as the input facts change. Certain (combinations…
Incremental Maintenance of DatalogMTL Materialisations
DatalogMTL extends the classical Datalog language with metric temporal logic (MTL), enabling expressive reasoning over temporal data. While existing reasoning approaches, such as materialisation based and automata based …
Optimised Maintenance of Datalog Materialisations
To efficiently answer queries, datalog systems often materialise all consequences of a datalog program, so the materialisation must be updated whenever the input facts change. Several solutions to the materialisation upd…
Capability Safety as Datalog: A Foundational Equivalence
We prove that capability safety admits an exact representation as propositional Datalog evaluation (Datalogprop: the monadic, ground, function-free fragment of first-order logic), enabling the transfer of algorithmic and…