Minimum-Cost Design of Auto-Scaling Server Farms Providing Reliability Guarantees

As next-generation mobile networks increasingly rely on virtualized infrastructure to deliver critical services, it is critical to ensure the efficiency of server farms while ensuring a reliable service. In fact, these server farms must meet stringent reliability guarantees to support time-sensitive applications in emerging 5G and beyond networks. In this paper, we tackle the optimal design of auto-scaling server farms, i.e., the selection of the best server type (and corresponding number of servers), taking into account both the service requirements and the operational and infrastructure costs. To achieve this, we develop an optimization algorithm that integrates (i) a model based on queueing theory to estimate the resources required to support the reliability constraints, and (ii) a general cost model including both capital and operational expenditures, which is minimized. We validate our approach through extensive simulations, comparing it against a benchmark based on classical queueing theory and exhaustive numerical searches. Results show that our method identifies the optimal server deployment in most cases while significantly reducing computation time, making it a practical solution for network planning.