Databelt: A Continuous Data Path for Serverless Workflows in the 3D Compute Continuum

2025-08-21

AI Summary

To address high latency and excessive network overhead in serverless workflows across 3D computing continua (edge–cloud–space), particularly under dynamic satellite link switching where state access involves numerous hops and severe redundant transmissions, this paper proposes the Continuous Data Path framework. Methodologically, it introduces: (i) an SLO-aware state propagation mechanism enabling on-demand, low-latency cross-tier state migration; and (ii) a runtime-aware state pre-offloading and function-state fusion mechanism to support in-orbit state sharing and collaborative state acquisition. The framework jointly optimizes state scheduling across heterogeneous multi-tier architectures. Experimental evaluation demonstrates that, compared to baseline approaches, the framework reduces workflow execution time by up to 66%, improves throughput by 50%, and decreases storage operation latency by up to 20%.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

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
• Economics, Online Markets and Human Computation: Architectures and workflows that use LLMs for crowd work

Abstract

Typically, serverless functions rely on remote storage services for managing state, which can result in increased latency and network communication overhead. In a dynamic environment such as the 3D (Edge-Cloud-Space) Compute Continuum, serverless functions face additional challenges due to frequent changes in network topology. As satellites move in and out of the range of ground stations, functions must make multiple hops to access cloud services, leading to high-latency state access and unnecessary data transfers. In this paper, we present Databelt, a state management framework for serverless workflows designed for the dynamic environment of the 3D Compute Continuum. Databelt introduces an SLO-aware state propagation mechanism that enables the function state to move continuously in orbit. Databelt proactively offloads function states to the most suitable node, such that when functions execute, the data is already present on the execution node or nearby, thus minimizing state access latency and reducing the number of network hops. Additionally, Databelt introduces a function state fusion mechanism that abstracts state management for functions sharing the same serverless runtime. When functions are fused, Databelt seamlessly retrieves their state as a group, reducing redundant network and storage operations and improving overall workflow efficiency. Our experimental results show that Databelt reduces workflow execution time by up to 66% and increases throughput by 50% compared to the baselines. Furthermore, our results show that Databelt function state fusion reduces storage operations latency by up to 20%, by reducing repetitive storage requests for functions within the same runtime, ensuring efficient execution of serverless workflows in highly dynamic network environments such as the 3D Continuum.

Problem

• Reducing latency in serverless workflows across dynamic 3D compute continuum
• Minimizing network hops for state access in edge-cloud-space environments
• Eliminating redundant data transfers for functions sharing runtime

Innovation

• SLO-aware state propagation mechanism
• Proactive offloading to suitable nodes
• Function state fusion for shared runtime