Server Placement with Shared Backups for Disaster-Resilient Clouds

TL;DR

This paper presents an optimization approach for server placement in geo-distributed disaster-resilient clouds, reducing backup server requirements by at least 40% while ensuring backup and primary VM separation and latency constraints.

Contribution

It introduces a novel optimization model for server placement that minimizes backup servers while guaranteeing disaster resilience and latency requirements in wide area networks.

Findings

Reduces backup server count by at least 40% in real topologies.

Ensures backup and primary VM separation to prevent simultaneous failures.

Addresses latency constraints in backup service deployment.

Abstract

A key strategy to build disaster-resilient clouds is to employ backups of virtual machines in a geo-distributed infrastructure. Today, the continuous and acknowledged replication of virtual machines in different servers is a service provided by different hypervisors. This strategy guarantees that the virtual machines will have no loss of disk and memory content if a disaster occurs, at a cost of strict bandwidth and latency requirements. Considering this kind of service, in this work, we propose an optimization problem to place servers in a wide area network. The goal is to guarantee that backup machines do not fail at the same time as their primary counterparts. In addition, by using virtualization, we also aim to reduce the amount of backup servers required. The optimal results, achieved in real topologies, reduce the number of backup servers by at least 40%. Moreover, this work highlights several characteristics of the backup service according to the employed network, such as the fulfillment of latency requirements.