Dolphin: An Actor-Oriented Database for Reactive Moving Object Data Management

Novel reactive moving object applications require solutions to support object reactive behaviors as a way to query and update dynamic data. While moving object scenarios have long been researched in the context of spatio-temporal data management, reactive behavior is usually left to end-user implementations. However, it is not just a matter of hardwiring reactive constraints: the required solutions need to satisfy tight lowlatency computation requirements and be scalable. This emerging class of applications builds on database technology, but implements substantial data management logic in the application tier. This paper explores a novel approach to enrich a distributed actor-based framework with reactive functionality and complex spatial data management along with concurrency semantics. Our goal is to better meet the needs of reactive moving object applications. Our approach relies on a proposal of the moving actor abstraction, which is a conceptual enhancement of the actor model with reactive sensing, movement, and spatial querying capabilities. This enhancement helps developers of reactive moving object applications avoid the significant burden of implementing application-level schemes to balance performance and consistency. Based on moving actors, we define a reactive moving object data management platform, named Moving Actor-Oriented Databases (MAODBs), and build Dolphin ��� an implementation of M-AODBs. Dolphin embodies a non-intrusive actor-based design layered on top of the Microsoft Orleans distributed virtual actor framework. In a set of experimental evaluations with realistic reactive moving object scenarios, Dolphin exhibits scalability on multi-machines and provides near-real-time reaction latency.
Work partially conducted in the context of the Future Cropping partnership [Future Cropping], supported by Innovation Fund Denmark. Experimental evaluation supported by the AWS Cloud Credits for Research program. In addition, this work was partly supported by the project "Modeling and Developing Actor Database Applications", funded by the Danish Agency for Science and Higher Education (number 7059-000528) and by FAPESP CEPID CCES 13/08293-7. Additional funding provided by FAPESP projects 19/074709 (Geo-spatial processing of IOT streams in digital agriculture: the case for actor database systems) and 17/02325-5, and by CNPq-Brazil projects 428459/2018-8 and 308018/2021-4.