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

2025-11-13

AI Summary

Existing reactive mobile object systems require end users to manually implement complex reactive logic, making it difficult to simultaneously achieve low latency and high scalability. To address this challenge, this paper proposes M-AODB—a novel database architecture that unifies reactive behavior modeling with spatiotemporal data management. Its core innovation is the “mobile actor” abstraction, which embeds state awareness, mobility modeling, and spatial query capabilities directly into a distributed virtual actor model. Built non-intrusively atop Microsoft Orleans, the framework integrates lightweight concurrency control and efficient spatiotemporal indexing. Experimental evaluation of the Dolphin prototype demonstrates millisecond-scale response latency and near-linear scalability across multi-node clusters. Consequently, M-AODB significantly improves both development efficiency and runtime performance for reactive mobile applications.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search

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.

Problem

• Managing reactive behaviors in moving object applications with low latency
• Integrating spatial data management with distributed actor frameworks
• Simplifying development of scalable reactive systems with consistency guarantees

Innovation

• Actor-based framework with reactive sensing capabilities
• Moving Actor abstraction for spatial querying and movement
• Non-intrusive design layered on distributed virtual actors