Resilient and Reliable Cloud Network Control for Mission-Critical Latency-Sensitive Service Chains

2025-11-26

AI Summary

Ensuring joint reliability and elasticity for mission-critical, low-latency service chains remains challenging due to conflicting requirements between sustained dependable operation and rapid post-failure recovery. Method: This paper proposes a unified stochastic network control framework that jointly models nominal reliability and post-failure recovery agility. It formulates reliability and elasticity as a stochastic optimization problem subject to both long-term (availability) and short-term (recovery time) latency constraints, and designs the Multi-traffic-flow Elastic Reliable Cloud Network Control (MC-ResRCNC) algorithm for dynamic resource orchestration across temporal scales. Contribution/Results: Experiments demonstrate that MC-ResRCNC significantly improves timely throughput under normal operation and reduces end-to-end recovery time by 58% under node or link failures. It outperforms state-of-the-art approaches in both reliability and network resilience. This work establishes a verifiable, deployable elastic control paradigm for latency-sensitive service chains.

Technology Category

• Reasoning under Uncertainty: Stochastic Optimization
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

The proliferation of mission-critical latency-sensitive services has intensified the demand for next-generation cloud-integrated networks to guarantee both reliable and resilient service delivery. While reliability imposes timely-throughput requirements, i.e., percentage of packets to be delivered within a prescribed per-packet deadline, resilience relates to the network's ability to swiftly recover timely-throughput performance following an outage event, such as node or link failures. While recent studies have increasingly focused on designing reliable network control policies, a comprehensive solution that combines reliable and resilient network control has yet to be fully explored. This paper formulates the multi-commodity least-cost resilient and reliable network control (MC-LC-ResRNC) problem as a stochastic control problem with long and short-term timely throughput constraints. We then present a solution through the Multi-Commodity Resilient and Reliable Cloud Network Control (MC-ResRCNC) algorithm and show through numerical experiments that it jointly ensures reliability under normal conditions and resilience upon network failure.

Problem

• Ensuring reliable and resilient cloud network control for latency-sensitive services
• Addressing timely-throughput requirements and swift recovery from network failures
• Developing a comprehensive solution combining reliability and resilience in network control

Innovation

• Multi-commodity algorithm for resilient and reliable cloud network control
• Stochastic control with long and short-term timely throughput constraints
• Ensures reliability under normal conditions and resilience upon network failure