Dolphin: An Actor-Oriented Database for Reactive Moving Object Data Management
Yiwen Wang, Vivek Shah, Marcos Antonio Vaz Salles, Claudia Bauzer Medeiros, Julio Cesar Dos Reis, Yongluan Zhou
TL;DR
The paper introduces Moving Actor Abstraction and Moving Actor-Oriented Databases (M-AODBs), culminating in Dolphin, a cloud-ready implementation on Microsoft Orleans that supports reactive, spatially aware moving objects at scale. It defines two concurrency semantics—Actor-Based Freshness for low-latency, up-to-date results and Actor-Based Snapshot for globally consistent views—and demonstrates their integration in move, query, and reactive workflows. Dolphin employs per-cell indexing, monitoring, and snapshot coordination, with a pluggable Moving Actor API to enable heterogeneous behaviors. Experimental results on synthetic and C-ITS benchmarks show near-real-time reactions, strong scalability across machines, and resilience under spatial skew, underscoring the practicality of the approach for reactive moving object applications.
Abstract
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 complex end-user implementations. However, it is not just a matter of hardwiring reactive constraints: the required solutions need to satisfy tight low-latency computation requirements and be scalable. 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 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 (M-AODBs), 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.