Alexander Wolosewicz

PhD Student at Illinois Institute of Technology
Contact: awolosewicz@hawk.illinoistech.edu
Github: https://github.com/awolosewicz

Bio: I graduated from Illinois Institute with my B.S. in Computer Science in May, 2023. I returned to IIT to pursue a PhD in January, 2024, and I am currently working towards that degree. My focus is in networking and security, with my current work focused on improving visibility in virtual networks.

My Work:

Recent News:

• October 2025: Attended the KNIT 11 workshop for the FABRIC testbed and gave a presentation for CREASE showcasing the development over the past year. This included two demos, for a small and large FABRIC topology, which are available as artifacts: small and large. The slides can be found here.
• September 2025: "Network Replay and Consistency Across Testbeds" accepted to INDIS '25 at SC25. This paper explores using middle-boxes that can buffer and replay traffic for debugging in virtual environments, and I provide a metric for quantifying the consistency of a network's behavior. My evaluations across local bare metal and the FABRIC testbed show how my tool and metric allow for effectively measuring and comparing network consistency, and reveal cases where virtual networks are not consistent with bare metal ones. A FABRIC artifact for reproducing the findings and exploring the tool can be found here.
• April 2025: As part of CREASE, designed and helped run a user evaluation for the network debugging fork of fablib. The evaluation involved 22 participants with varying levels of experience with networks and FABRIC, and we found that users with some experience in both networks and FABRIC were able to complete debugging tasks up to 37.5% faster with the tool than without it.
• March 2025: Gave a presentation on a 2-page paper on the network debugging fork of Fablib at LATTE'25 (ASPLOS workshop). Since the KNIT10 presentation, this included timing statistics on the overhead the monitors introduce, after they had been converted to be DPDK-driven instead of P4-BMv2. The slides can be found here.
• March 2025: Presented at FABRIC's KNIT10 workshop about the development of my Fablib fork to improve network debugging on FABRIC. The tool is designed to provide an easier and faster method of debugging a network at once, from a single position, in a manner that does not require explicit user support or specific hardware. The current foundation of the tool inserts "monitor" nodes on user-specified links, which stamp traffic with unique IDs and forward a copy of the packet location, time, headerstack, and ID to a central database. This database thus stores a history of packets as they cross and are transformed by the network, and can be queried by users to locate the source of network errors. The slides for the presentation can be found here. The poster shown at Demo Night:
  
• December 2024: As part of an AI/ML course, I alongside other students evaluated the performance of a Random Forest and Neural Network model on classifying traffic as DDoS attacks using the BCCC-cPacket-Cloud-DDoS-2024 dataset. This produced a 6 page report and python notebooks for the Neural Network and Random Forest. My contributions were primarily to the Neural Network and much of the final report.
• October 2024: "Experience Report: Using the FABRIC Testbed to teach a Graduate Computer Networking course" accepted as a paper to SIGCSE TS 2025.
• September 2024: "Combining Attestation and Provenance to Improve Reproducibility and Debugging on FABRIC" Demo/Poster at MERIF24.
  
• August 2024: First beta of CREASE released, which includes a copy of my attestable switch, and deployed to every FABRIC node, including international ones.
• April 2024: "Attestation-Capable, Programmable Switch as 5G UPF" Demo/Poster at HoTSoS 2024.
  
• March 2024: "Attestation-Capable, Programmable Switch as 5G UPF" Demo/Poster at KNIT8.
  
• November 2023: "Testbed Evaluation of an Attestation-Capable, Programmable Software Switch" short paper at INDIS Workshop, SC23.
  This was presented by Nishanth Shyamkumar (co-author) and he received the Best Demo award.
  A recording of his demo can be found here.