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Titel:

ADFAT: Adversarial Flow Arrival Time Generation for Demand-Oblivious Data Center Networks

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Schmidt, Sebastian; Zerwas, Johannes; Kellerer, Wolfgang
Abstract:
Researchers developing new architectures and algorithms for data center networks (DCNs) face the challenge of producing meaningful evaluations of their contributions. Traditional evaluation methods like traffic traces and parametric models can fail to reveal weak spots in DCNs. The concept of adversarial inputs shapes traffic data, making it challenging for a DCN to serve it. Adversarial traffic can provide insight into performance issues of a DCN that might go unnoticed with traces and models....     »
Kongress- / Buchtitel:
19th International Conference on Network and Service Management (CNSM 2023)
Jahr:
2023
Volltext / DOI:
doi:https://doi.org/10.23919/CNSM59352.2023.10327896
TUM Einrichtung:
Lehrstuhl für Kommunikationsnetze
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