GHDC : a dual-centric data center network architecture by using multi-port servers with greater incremental scalability

As the volume of data keeps growing rapidly, more and more storage devices, servers, and network devices are continuously added into data center networks (DCNs) to store, manage, and analyze the data. The industry experience indicates that, instead of adding a huge number of servers into the DCNs at a time, the DCN can also be expanded gradually by adding a small number of servers from time to time. This paper proposes a new type of dual-centric data center network structure, called GHDC (Generalized Hypercube Data Center network architecture), which is constructed by using commodity switches and multi-port servers. After analyzing the shortest distance between any two vertices, a routing algorithm for GHDC is developed. To achieve incremental scalability, two incomplete GHDC structures are proposed. A small number of servers can be added into the incomplete GHDC structures while their topological properties are maintained. The analysis and experiment results show that GHDC significantly outperform the other DCN structures, such as FatTree , BCube , Platonica , FCell , FSquare , and FRectangle , in terms of the incremental scalability and robustness. The average throughput of GHDC is approximately comparable to that of FatTree , BCube , and FSquare , and is higher than that of Platonica , FCell , and FRectangle by about 130.2%, 17.45% and 25.5%. Compared with the FatTree , BCube , FCell , FRectangle , and FSquare , GHDC reduces the cost by about 68.49%, 78.04%, 10.84%, 22.85%, and 29.55%, and reduces the max energy consumption by about 69.45%, 34.48%, 11.55%, 24.31%, and 29.58%, respectively. The actual energy consumption of GHDC is much lower than that of FatTree , BCube , FCell , FRectangle , and FSquare , and is little higher than that of Platonia .