High throughput path selection for unstructured data center networks

The increase in demand and popularity of cloud and big data applications has driven the need for higher throughput data center network design. Recent work to provide topologies with much denser interconnects pose a difficult challenge for routing of traffic within a data center. Even with proposals like MPTCP that improve upon TCP, there is a still a gap between theoretical throughput and empirical throughput. Our goal is to study routing in data centers at both flow and packet-level to determine the cause of inefficiency and study methods of path selection that may help bridge the gap between optimal throughput and packet level throughput. The difference in throughput can be attributed to inefficiency due to path selection and inefficiency due to protocol overhead; we quantify the contribution of each. Focusing on path selection, our experiments show that k-disjoint paths provide much better throughput in most topologies than the previously used k-shortest paths. We also show that one can positively impact network throughput by varying the number of paths according to network density.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2013

Author dc:creator

• Sharma, Abhishek

Contributors dc:contributor

• Godfrey, Philip B.

• Data Center
• Multipath Transmission Control Protocol (MPTCP)
• Jellyfish
• Shortest Paths
• Disjoint Paths
• Throughput
• Random Regular Graph (RRG)
• Random Permutation Matrix
• Switches
• Servers
• Ports
• Network Density

Statement dc:rights

• Copyright 2013 Abhishek Sharma. All rights reserved

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/45451

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/45451