Optimal Cloud Network Control with Strict Latency Constraints

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.

Optimal Multicast Service Chain Control: Packet Processing, Routing, and Duplication

“…On contrary, distributed fluid-based algorithms only require local information exchange and decision making, and while they can suffer from inefficient loopy routes in low congestion scenarios, they are especially suitable for high congestion regimes. Besides, a recent study [13], [14] proposes a distributed, backpressure-fashioned network control policy, which is designed to support services with stringent latency constraints.…”