Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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    Dynamics of TCP Congestion Avoidance with Random Drop and Random Marking Queues
    (2000) Misra, Archan; Baras, John S.; ISR; CSHCN
    Development and deployment of newer congestion feedback measures such as RED and ECN provide us a significant opportunity for modifying TCP response to congestion. Effective utilization of such opportunities requires detailed analysis of the behavior of congestion avoidance schemes with such randomized feedback mechanisms.

    In this dissertation, we consider the behavior of generalized TCP congestion avoidance when subject to randomized congestion feedback, such as RED and ECN. The window distribution of individual flows under a variable packet loss/marking probability is established and studied to demonstrate the desirability of specifying a less drastic reduction in the window size in response to ECN-based congestion feedback.

    A fixed-point based analysis is also presented to derive the mean TCP window sizes (and throughputs) and the mean queue occupancy when multiple such generalized TCP flows interact with a single bottleneck queue performing randomized congestion feedback.

    Recommendations on the use of memory (use of weighted averages of the past queue occupancy) and on the use of "drop biasing" (minimum separation between consecutive drops) are provided to reduce the variability of the queue occupancy.

    Finally, the interaction of TCP congestion avoidance with randomized feedback is related to a framework for global optimization of network costs. Such a relation is used to provide the theory behind the shape of the marking (dropping) functions used in a randomized feedback buffer.