Minimizing cost of provisioning in fault-tolerant distributed data centers with durability constraints

Many popular e-commerce applications run on geo-distributed data centers requiring high availability. Fault-tolerant distributed data centers are designed by provisioning spare compute capacity to support the load of failed data center, apart from ensuring data durability. The main challenge during the planning phase is how to provision spare capacity such that the total cost of ownership (TCO) is minimized. While the literature handled spare capacity provisioning by minimizing the number of servers, variation in electricity cost and PUE corroborate the need to minimize the operating cost for capacity provisioning. We develop an MILP model for spare capacity provisioning for geo-distributed data centers with durability requirements. We consider spare capacity provisioning problem with the objective of minimizing TCO. We model variation in the demand, fluctuation in electricity prices across locations, cost of state replication, carbon tax across different countries, and delay constraints while formulating the optimization model. Solving the model shows that TCO is reduced while leveraging the electricity price variation and demand multiplexing. The proposed model outperforms the CDN model by 50% and the minimum server model by 34%. Results also demonstrate the effect of power usage effectiveness (PUE), latency, number of data centers and demand on the TCO.