Towards cost-effective capacity provisioning for fault-tolerant green distributed data centers

Many critical e-commerce and financial services predominantly depend on geo-distributed data centers for scalability and availability. Recent market surveys show that failure of a data center is inevitable causing huge financial loss. Fault-tolerant distributed data centers are typically designed by provisioning spare capacity to mask failure at a site. At the same time, data center operators are trying to reduce their carbon footprint by using renewable energy power. Thus, a key challenge in spare capacity provisioning is to distribute the additional servers across the sites, minimizing the total cost of ownership (which includes the server acquisition cost and operating cost) while maximizing the usage of renewable energy. While the existing models minimize the number of servers, we demonstrate that brown electricity price and renewable energy availability should be considered for sustainable fault tolerant data center design. We use mixed integer linear programming formulation to minimize the total cost of ownership (TCO), while handling constraints such as delay bound, partial or complete failure, and intermittent supply of renewable energy. By solving the optimization problem, we demonstrate that the proposed model reduces the TCO by 48% compared to CDN model (minimize latency), and by 24% compared to minimum server model (minimizes server cost). Results also highlight the impact of latency, number of data centers, failure percentage, and demand variation on the TCO.