Extending Data Spatial Semantics for Scale Agnostic Programming

2025-04-04

AI Summary

This paper addresses the semantic limitations of Data Space Programming (DSP) in scaling. We propose a scale-invariant programming paradigm that decouples runtime concerns—such as persistence, multi-user collaboration, and cross-machine distribution—from application logic. Our core method introduces a global root node and optional walker entry points, embedding scalability as an intrinsic property of DSP’s topological semantics. By formally defining abstract persistent state, multi-user contexts, multiple entry points, and distributed primitives, we achieve “write once, execute at any scale”: a single program automatically adapts to heterogeneous environments—including single- vs. multi-user, local vs. distributed, and ephemeral vs. persistent deployments. This work is the first to systematically integrate scale invariance into the semantic layer of DSP, thereby significantly enhancing application portability and developer productivity.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

We introduce extensions to Data Spatial Programming (DSP) that enable scale-agnostic programming for application development. Building on DSP's paradigm shift from data-to-compute to compute-to-data, we formalize additional intrinsic language constructs that abstract persistent state, multi-user contexts, multiple entry points, and cross-machine distribution for applications. By introducing a globally accessible root node and treating walkers as potential entry points, we demonstrate how programs can be written once and executed across scales, from single-user to multi-user, from local to distributed, without modification. These extensions allow developers to focus on domain logic while delegating runtime concerns of persistence, multi-user support, distribution, and API interfacing to the execution environment. Our approach makes scale-agnostic programming a natural extension of the topological semantics of DSP, allowing applications to seamlessly transition from single-user to multi-user scenarios, from ephemeral to persistent execution contexts, and from local to distributed execution environments.

Problem

• Enabling scale-agnostic programming for diverse application development
• Abstracting persistent state and multi-user contexts in spatial programming
• Seamless transition from local to distributed execution environments

Innovation

• Extends DSP with scale-agnostic programming constructs
• Introduces globally accessible root node and walkers
• Abstracts persistence, distribution, and multi-user support