Air-ground vehicle networking double-time-scale scheduling method based on situation awareness

By employing a dual-timescale orchestration method based on situational awareness, a network-level situational state is constructed and combined with long-term and short-term protection strategies. This addresses the instability of task flow execution in air-ground cooperative vehicle-to-everything (V2X) environments, enabling efficient, reliable, and flexible execution of task flows.

CN122227201APending Publication Date: 2026-06-16JIANGXI UNIV OF SCI & TECH +2
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JIANGXI UNIV OF SCI & TECH
Filing Date
2026-04-24
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

In the air-ground cooperative vehicle-to-everything (V2X) edge-cloud continuum environment, existing technologies struggle to balance long-term protection configurations with short-term online recovery, resulting in complex task flows in dynamic environments with issues such as high task completion latency, high recovery costs, insufficient survivability, and risk of defaulting on deadlines.

⚗Method used

A situational awareness-based dual-timescale orchestration method is adopted. By constructing a network-level situational state and combining long-term protection strategies and short-term online recovery mechanisms, the collaborative optimization of task mapping, resource allocation, and online recovery is achieved, including checkpoint configuration, backup resource reservation, and online recovery process.

🎯Benefits of technology

It improves the execution stability and reliability of complex task flows in dynamic heterogeneous environments, meets the constraints of computing capacity, link bandwidth, survivability and energy security, and achieves adaptive and elastic execution.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a kind of based on situation awareness's air-ground vehicle networking double time scale arrangement method. First, the air-ground vehicle networking edge cloud collaborative execution environment consisting of roadside edge server, unmanned aerial vehicle air edge node and cloud node is constructed, and business is modeled as the directed acyclic graph DAG workflow with task dependency relationship. Secondly, the local observation information such as link communication quality, service processing capacity, fault danger exposure and energy state of each computing node is collected, and network level situation state for unified scheduling decision is generated by time smoothing, neighborhood fusion and uncertainty calibration. Then, based on the network level situation state and execution trajectory, checkpoint configuration, backup resource reservation, recovery mode preference and deadline tail risk budget are updated on slow time scale, and ready task main execution node selection, backup node selection, transmission path selection, communication resource allocation, computing resource allocation and recovery action selection are executed on fast time scale;When detecting node failure, task deadline cannot be met or communication contact relationship fails, trigger backup switching, checkpoint playback, path re-routing or task migration and other online recovery processes. Finally, according to task actual execution result, update physical task queue, virtual risk queue, unmanned aerial vehicle residual energy state and execution trajectory set, form the closed-loop arrangement mechanism of protection adaptive and online recovery collaborative coupling.
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