Robust Sketch Orchestration in Programmable Networks

Simple item page
dc.contributor.advisorGhaderi, Majid
dc.contributor.authorErfanmanesh, Zeinab
dc.contributor.committeememberWang, Mea
dc.contributor.committeememberFapojuwo, Abraham
dc.date2025-02
dc.date.accessioned2025-01-30T15:44:37Z
dc.date.available2025-01-30T15:44:37Z
dc.date.issued2025-01-15
dc.description.abstractAs modern networks grow in scale and speed, sketch-based algorithms have become essential for achieving accurate and low-overhead network monitoring. These algorithms enable efficient data summarization, allowing network operators to monitor traffic patterns without placing significant computational or memory demands on network devices. However, existing solutions for sketch-based network monitoring assume that traffic rates are fixed and known in advance. This assumption, while simplifying the monitoring process, fails to reflect the dynamic nature of real-world traffic, leading to degraded monitoring accuracy. In this thesis, we propose a novel approach for coordinated sketch placement on programmable network devices, such as switches and SmartNICs, without relying on the fixed traffic rate assumption. Instead, we consider scenarios where only statistical information about traffic rates, such as their means and variances, is available. To this end, we show that the problem can be formulated as an integer second-order cone program (ISOCP). Given the computational challenges of solving such optimization problems, especially in large-scale networks, we introduce an approximation technique to transform the problem into a linear formulation. This approximation not only reduces computational complexity but also enables efficient solutions for large instances of the problem using standard optimization tools. Our evaluations, conducted with realistic workloads and network configurations, demonstrate that, by accounting for dynamic traffic rates, our approach can increase monitoring accuracy in the network by up to 2× across different workloads compared to the existing solutions that do not explicitly consider these dynamics.
dc.identifier.citationErfanmanesh, Z. (2025). Robust sketch orchestration in programmable networks (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.urihttps://hdl.handle.net/1880/120500
dc.language.isoen
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgary
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectNetwork monitoring
dc.subjectOptimization
dc.subjectDynamic Flow Rates
dc.subject.classificationComputer Science
dc.titleRobust Sketch Orchestration in Programmable Networks
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.thesis.accesssetbystudentI do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible.
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2025_erfanmanesh_zeinab.pdf
Size:
1.45 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations