London Design Gold

2025

Edge-Cloud Collaborative Access CR Intell Sched Platform

Entrant

Fujian Zixun Information Technology Co., Ltd.-Lin Xi

Category

Conceptual Design - Smart Technologies

Client's Name

Country / Region

China

By constructing a multi-tenant instance management framework, a full-lifecycle operation auditing system, and security control modules for peripherals and files, the Intelligent Scheduling Platform for Computing Resources Based on Edge-Cloud Collaborative Access achieves unified management and security isolation of edge-side virtual machine instances, disk images, USB devices, and shared files. The platform supports remote instance access, real-time monitoring, and operation video playback via the web interface. Combined with file transfer review, fine-grained permission policies, and log tracking, it comprehensively ensures the controllability and compliance of edge business resource access.

The platform specifically addresses core pain points in edge computing scenarios—including rigid instance resource allocation, lack of auditing for user operations, and security risks in peripheral mounting and file sharing—meeting enterprises' high management demands for flexible resource allocation and secure behavior auditing. Traditional edge node management models suffer from low efficiency in instance creation and cloning, scattered operation logs, and difficulty in rapid tracing and accountability for security incidents, failing to adapt to enterprises' refined management requirements.

Leveraging instance snapshot and image rapid deployment, fine-grained permission control for clipboards and USB devices, real-time screen recording, and comprehensive operation log documentation, the platform significantly enhances the management efficiency and security protection of edge instances. It supports batch creation, cloning, suspension, and rapid recovery of instances; audit videos can be automatically cleaned up, retrieved, and played back according to policies; file transfers include upload, download, and multi-level review processes, effectively preventing unauthorized data leakage. In terms of resource management granularity, operational audit integrity, multi-tenant isolation, and security compliance support capabilities, the platform outperforms the traditional decentralized operation and maintenance methods for edge nodes, providing a feasible implementation path for secure and controllable resource management in edge computing environments.

Credits

Chief Designer
Lin Xi
More Gold Winners
UX Design
2025
London Design Awards - Pixel Pack AI Platform
Pixel Pack Inc

Entrant

Fang Nan & Tianyang Chen

Category

User Experience Design (UX) - Best Use of AI & Machine Learning

Product
2025
London Design Awards - Accurate CT & Lux Lamp

Entrant

Simon Wang

Category

Product Design - Lighting

Product
2025
London Design Awards - The Wave

Entrant

Mikuihua (Beijing) Pet Products Co., Ltd.

Category

Product Design - Pet

Interior
2025
London Design Awards - Yueyang Xingchang R&D Center

Entrant

T1D Space Design

Category

Interior Design - Office