Two-Aggregator Topology Optimization Using Single Paths in Data Center Networks

This paper focuses on the data aggregation problem to two aggregators in a data center network under the constraint that each source rack must use a single path to each aggregator. We derive bounds on the approximation ratios of two classes of aggregation algorithms- Restricted 1-Round (R1R) and Restricted 2-Round (R2R). We achieve tighter bounds for the problem with additional constraints on the inputs. We propose another strategy using the 2Chain topology for k = 2, where k denotes the maximum degree of each top-of-rack(ToR) switch (number of uplinks in a ToR switch) in the data center and show that the optimal 2Chain cannot have an aggregation time greater than that of the optimal R1R and R2R topologies. For k >= 4, we propose a 1-round aggregation algorithm (1R) that uses trees for aggregation. Experimental results illustrate that 1R, R2R and R1R reduce the aggregation time by up to 85, 67 and 67 percent respectively for k = 4 relative to the two-round aggregation algorithm proposed by Wang et al. Moreover, for k = 2, the 2Chain can reduce the aggregation time up to 42 and 24 percent respectively relative to R1R and R2R.

Automated summary

This paper focuses on the data aggregation problem in a data center network, proposing two different algorithms and deriving various approximation ratios under different input constraints. Experimental results show that the proposed algorithms can significantly reduce the aggregation time compared to existing algorithms.