A Resilient Framework for Security-Integrated Resource Scheduling in Distributed Clouds

Abstract

As the scale and complexity of distributed cloud environments continue to grow, ensuring efficient resource scheduling while maintaining stringent security standards has become a pivotal concern. The distributed nature of cloud computing introduces several challenges, including latency, resource heterogeneity, dynamic workloads, and security threats that span across geographically dispersed data centers. Traditional scheduling frameworks often prioritize performance and cost-efficiency, overlooking the integration of robust security mechanisms. This paper proposes a resilient framework for security-integrated resource scheduling that not only optimizes the allocation of resources across distributed cloud environments but also embeds security as a core component of the scheduling logic. The proposed model introduces an adaptive scheduling algorithm that accounts for security levels, threat contexts, and workload sensitivity while dynamically assigning tasks. The framework enhances resilience by mitigating risks through threat-aware decision-making and ensures service continuity even in the face of security anomalies. By combining resilience with intelligent resource management, the framework offers a holistic approach to secure and efficient operations in modern distributed clouds.