Multiobjective 3-D Topology Optimization of Next-Generation Wireless Data Center Network

Abstract

As one of the next-generation network technologies for data centers, wireless data center networks have important research significance. Smart architecture optimization and management are vital for wireless data center networks. With the ever-increasing demand for data center resources, the deployment of the data servers are on the rise. However, traditional wired links among servers are expensive and inflexible. Benefitting from the development of intelligent optimization and other techniques, this article studies a high-speed wireless topology for wireless data center networks. A radio propagation model based on a heat map is constructed. The line-of-sight issue and the interference problem are also discussed. By simultaneously considering the objectives of coverage, propagation intensity, and interference intensity, as well as the constraint of connectivity, the topology optimization problem is formulated as a multiobjective optimization problem. To seek the solutions, several state-of-the-art serial multiobjective evolutionary algorithms (MOEAs), as well as parallel MOEAs, are employed. Prior knowledge is preferred for the grouping, and parameter adaptation is conducted in the distributed parallel algorithms. Experimental results demonstrate that the parallel MOEAs perform effectively in the optimization results and efficiently in time consumption.