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

TL;DR

This paper introduces a novel control algorithm for cloud networks that guarantees both reliability and resilience for mission-critical latency-sensitive services, ensuring performance during normal operation and after failures.

Contribution

It formulates a comprehensive stochastic control problem and proposes the MC-ResRCNC algorithm to jointly optimize reliability and resilience in cloud network control.

Findings

Ensures reliability under normal network conditions.

Provides resilience and quick recovery after outages.

Demonstrates effectiveness through numerical experiments.

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.