Optimal Cloud Network Control with Strict Latency Constraints

TL;DR

This paper develops a distributed control algorithm for cloud networks that guarantees strict packet deadlines, minimizing resource costs while ensuring timely delivery of latency-sensitive services.

Contribution

It introduces a novel queuing model with packet lifetime tracking and applies Lyapunov optimization to derive a near-optimal, fully distributed control policy for deadline-constrained cloud networks.

Findings

The proposed control policy outperforms existing methods in delivery success rate.

Numerical results confirm the near-optimality and efficiency of the algorithm.

The approach effectively manages strict latency constraints in cloud network control.

Abstract

The timely delivery of resource-intensive and latency-sensitive services (e.g., industrial automation, augmented reality) over distributed computing networks (e.g., mobile edge computing) is drawing increasing attention. Motivated by the insufficiency of average delay performance guarantees provided by existing studies, we focus on the critical goal of delivering next generation real-time services ahead of corresponding deadlines on a per-packet basis, while minimizing overall cloud network resource cost. We introduce a novel queuing system that is able to track data packets' lifetime and formalize the optimal cloud network control problem with strict deadline constraints. After illustrating the main challenges in delivering packets to their destinations before getting dropped due to lifetime expiry, we construct an equivalent formulation, where relaxed flow conservation allows leveraging Lyapunov optimization to derive a provably near-optimal fully distributed algorithm for the original problem. Numerical results validate the theoretical analysis and show the superior performance of the proposed control policy compared with state-of-the-art cloud network control.