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Virtual Node-Driven Cloud-Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors.

Xinyang Gu¹, Zhansheng Duan¹, Guangyuan Ye¹

¹Center for Information Engineering Science Research, Xi'an Jiaotong University, Xi'an 710049, China.

Sensors (Basel, Switzerland)

|January 25, 2025

Summary

This study introduces virtual node-driven resource scheduling to manage task congestion in visual surveillance systems. The proposed integer linear programming model effectively handles high workloads and limited resources, outperforming other algorithms.

Keywords:

cloud computing edge computing resource scheduling virtual node

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Area of Science:

Computer Science
Electrical Engineering
Network Security

Background:

Distributed surveillance systems are crucial for public security, utilizing visual sensors, edge, and cloud computing.
Resource scheduling is vital for system efficiency, balancing workloads to meet real-time monitoring and emergency response needs.
Existing research often overlooks task congestion caused by insufficient physical resources, focusing instead on Quality of Service (QoS), latency, and energy.

Purpose of the Study:

To address task congestion and resource limitations in visual surveillance systems.
To introduce and evaluate a novel virtual node-driven resource scheduling approach.
To develop and compare an integer linear programming (ILP) model against alternative algorithms for resource management.

Main Methods:

Introduction of virtual nodes to manage resource shortages.
Formulation of a convex-objective integer linear programming (ILP) model for resource scheduling.
Development of three benchmark algorithms: extended random, genetic, and heuristic algorithms.

Main Results:

All proposed scheduling algorithms effectively managed multiple priority tasks under resource constraints.
The ILP model demonstrated superior scheduling performance compared to the benchmark algorithms.
Virtual node-driven scheduling proved effective in mitigating task congestion in surveillance systems.

Conclusions:

The virtual node concept provides a viable solution for resource shortages in distributed surveillance.
The ILP model offers optimal scheduling performance for high-workload, resource-constrained environments.
This research enhances the robustness and efficiency of public security surveillance systems through advanced resource management.