A fundamental approach for providing service-level guarantees for wide-area networks
Name
1127386876-MIT.pdf
Size
2.1 MB
Format
Adobe PDF
Checksum (MD5)
cc1472ae968337da608e90f82b3af09e
Author(s)
Bogle, Jeremy(Jeremy P.)
Advisor(s)
Manya Ghobadi.
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
To keep up with the continuous growth in demand, cloud providers spend millions of dollars augmenting the capacity of their wide-area backbones and devote significant effort to efficiently utilizing WAN capacity. A key challenge is striking a good balance between network utilization and availability, as these are inherently at odds; a highly utilized network might not be able to withstand unexpected traffic shifts resulting from link/node failures. I motivate this problem using real data from a large service provider and propose a solution called TeaVaR (Traffic Engineering Applying Value at Risk), which draws on financial risk theory to realize a risk management approach to traffic engineering (TE). I leverage empirical data to generate a probabilistic model of network failures, and formulate a Linear Program (LP) that maximizes bandwidth allocation to network users subject to a service level agreement (SLA). I prove TeaVaR's correctness, and then compare it to state-of-the-art TE solutions with extensive simulations across many network topologies, failure scenarios, and real-world traffic patterns. The results show that with TeaVaR, operators can support up to twice as much throughput as other TE schemes, at the same level of availability. I also construct a simulation tool that builds on my implementation of TeaVaR and simulates its usage in the data plane. This tool can be useful not only for testing TE schemes but also for capacity planning, as it allows network operators to see how their network is performing, where the bottlenecks are, and what kind of demand loads it can handle.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 55-58).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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