A Layered and Aggregated Queuing Network Simulator for Detection of Abnormalities

Published

December 3, 2017

Author(s)

Junfei Xie, Chenyan He, Yan Wan, Kevin L. Mills, Christopher E. Dabrowski

Abstract

Driven by the needs to monitor, detect, and prevent catastrophic failures for complex information systems in real-time, we develop in this paper a discrete-time queuing network simulator. The dynamic model for the simulator abstracts network dynamics by taking an aggregated and layered structure. Comparative studies verify capabilities of the simulator in terms of accuracy and computational efficiency. We illustrate the model structure, flow processing mechanisms, and simulator implementation. We also illustrate the use of this simulator to detect distributed denial-of-service (DDoS) flooding attacks, based on a cross-correlation-based measure. Finally, we show that the layered structure provides new insights on the spatiotemporal spread patterns of cascading failure, by revealing spreads both horizontally within a sub-network and vertically across sub-networks.

Proceedings Title

Proceeding of the Winter Simulation Conference 2017

Conference Dates

December 3-6, 2017

Conference Location

Las Vegas, NV, US

Pub Type

Conferences

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DOI Link

Keywords

discrete-time queuing network model, layered networks, detection of DDoS attacks, cascading failures

Citation

Xie, J. , He, C. , Wan, Y. , Mills, K. and Dabrowski, C. (2017), A Layered and Aggregated Queuing Network Simulator for Detection of Abnormalities, Proceeding of the Winter Simulation Conference 2017, Las Vegas, NV, US, [online], https://doi.org/10.1109/WSC.2017.8247856 (Accessed October 16, 2025)