LAUSR

Data center networks (DCNs) continuously evolve to support emerging applications. For instance, server-centric architectures are becoming popular because they improve the modularity and resilience of data centers. In a server-centric DCN, switching functionalities are embedded in each server instead of in dedicated switches. Recently, wireless technologies have been introduced into the design of server-centric DCNs. Wireless interconnects provide great flexibility by creating direct flyways between servers. These wireless links help to reduce the length of paths assigned to flows so that fewer links must be powered-on to transfer data. In this paper, we investigate energy-aware scheduling of coflows and antenna directions in a server-centric DCN. Coflows are groups of parallel and high-volume flows generated by big data applications. We assume that the DCN is hybrid, i.e., that it includes both wired and wireless links. We formulate this scheduling problem as an optimization problem named energy-aware coflow and antenna scheduling (ECAS) and solve it using a mathematical programming solver. We further prove the NP-hardness of the formulated ECAS problem. We also introduce a heuristic algorithm to reduce the computational complexity. Our simulation results show that our optimal solution saves up to 48% of energy compared with representative competitors. Our heuristic algorithm achieves lower energy savings but still generates the shortest paths and lowest transferring time of flows. Further simulations on the network topology with a different size also confirm the efficiency of our proposed model and algorithm.