TY - GEN
T1 - On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols
AU - Liu, Qiang
AU - Rao, Nageswara
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/22
Y1 - 2019/1/22
N2 - Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex nonlinear manner, on the congestion control mechanism, buffer size, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity geometry of throughput profiles, which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profiles to characterize the overall performance of a transport protocol. These measurement-based analytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.
AB - Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex nonlinear manner, on the congestion control mechanism, buffer size, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity geometry of throughput profiles, which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profiles to characterize the overall performance of a transport protocol. These measurement-based analytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.
KW - Analytics
KW - Concavity
KW - Dedicated connections
KW - TCP
KW - Throughput profile
KW - UDT
KW - Utilization
UR - http://www.scopus.com/inward/record.url?scp=85060943257&partnerID=8YFLogxK
U2 - 10.1109/HPCC/SmartCity/DSS.2018.00088
DO - 10.1109/HPCC/SmartCity/DSS.2018.00088
M3 - Conference contribution
AN - SCOPUS:85060943257
T3 - Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018
SP - 430
EP - 438
BT - Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018
Y2 - 28 June 2018 through 30 June 2018
ER -