Data center network energy consumption minimization: a hierarchical FAT-tree approach

To meet the ever-growing cloud users’ demands, deployment of the large-scale datacenters has taken place and the numbers of servers have been increased exponentially. In modern years, there have been hasty growth of geographically distributed and large-scale data centers which is been deployed to support current users’ demands by the internet service operator. These datacenters consume enormous amount of electric power that includes servers, cooling-machines and networking switches, which leads to enormous challenges in the era of designing cost-effective and efficient data center network. In recent year, number of works proposed to overcome the above challenges in different direction. In this paper, different datacenter network-topologies have been investigated and a modified cost effective hierarchical Fat-Tree for building network-topology has been proposed. After this, we articulate the energy optimization problem as a MILP problem with an objective to minimize the amount of energy consumed in datacenter networks. Due to effective high computational complexity of MILP, an algorithm is proposed to deal with the problem of Several extensive simulation-based experiments are accompanied using an optimization solver (CPLEX) to evaluate and validate the effectiveness of the given proposed algorithm. The efficiency of the proposed model is shown by the several simulation-based results.