Multi-resource Aware Congestion Control in Data Centers

Abstract

Network has been widely reported as a bottleneck of data center applications. However, current researches of congestion control are unaware of multiple resources consuming and decrease all flows when congestion, ignoring some involved flows may not be the faults. In this paper, we propose a novel multi-resources aware congestion control framework MRTCP to provide a fine-grain control on flows when congestions appear. MRTCP exploits a multi-tuple vector model to measure multi-resources provision and consumption, and develops a novel metric RB (Resource Balance) to denote the heterogeneous amounts of resources employed by each flow. It analyzes which resources are being the bottlenecks that lead to congestions, calculates the responsibility of each flow to this congestion, and then adjusts their sending rates respectively. Our experiment results demonstrate that MRTCP is able to optimize network multi-resources utilization and improve network throughput without adding obvious packets delays.