Performance evaluation of massively parallel and high speed connectionless vs. connection oriented communication sessions

Abstract

In this paper we focus on the fast communication issues of the Big Data processing tasks shared between High Performance Computing systems. In our performance evaluation framework we designed and developed two traffic measurement tools in order to answer some theoretical questions related to congestion control in practice. The first one is based on iperf and tcpdump softwares to capture data flows of TCP and UDP sessions. Classification aspects of the measurement cases were: homogeneity of the traffics, number of parallel communication sessions, and implementation types of the TCP congestion control algorithm. Dozens of parallel traffic scenarios were executed in a dumbbell topology to evaluate effects of the massively parallel communication sessions in wireline local and metropolitan area networks. Since we found that connection oriented data transfer sessions have limited performance features during communication, we implemented a second communication tool named Fast Manager of File Transfer (FMFT). This application with transfer rate monitoring and regulation capability is based on parallel connectionless data transfer sessions supervised by a common connection oriented control session and provides better transfer rate than the classical file transfer mechanisms using TCP services. Methodology of the statistical analysis and highlights of this heterogeneous parallel communication mechanism are explained, too.