Fair Queueing

From: Kate Everitt (kteveritt@yahoo.com)
Date: Sun Oct 24 2004 - 20:53:09 PDT

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    Fair Queueing
    Review: Katherine Everitt

    This paper discusses the design and implementation of
    a fair queuing algorithm for network traffic. They
    define fair as meaning fair allocation of bandwidth,
    protection from badly behaved hosts, and lower delay
    for low traffic sources.

    The approach presented in the paper decouples
    bandwidth, buffer allocation, and packet waiting /
    when the packets get transmitted. It allocates these
    resources based on conversations, which are source
    destination pairs. Fair Queuing, or FQ, fixes two
    problems with previous approaches. Unlike FCFS (first
    come first serve), it does not drop packets based on
    last packet in. In FCFS, ill-behaved hosts can take
    over and fill up the buffers, causing problems for
    other hosts. (One observation I found really
    interesting in this paper was the idea that the ack
    from a packet can clue in a heavy sender that the
    queue is has a space, thus giving it an advantage over
    endpoints that send packets randomly.) The other
    problem FQ solved occurs with round robin queue
    scheduler. In this case, the problem of ill behaved
    hosts is partially solved, as bad hosts just fill up
    their own buffer. However, differing packet sizes can
    cause an unfair advantage, as everybody gets one
    packet per round robin schedule.

    FQ is very effective at solving these problems because
    it not only imposes an extra cost on ill behaved
    endpoints, it gives an advantage to services which
    don’t need as many resources. At one point I
    thought it might be valuable to tell the router if you
    wanted a particular class of service, ie send quickly
    but I won’t send much traffic, but then I
    realized this was implicit in FQ. If you send more
    traffic, it will be slower, if you need speed, send
    less.

     My only concerns with FQ are that it seems difficult
    to roll out gradually, because hosts may need to know
    what kind of scheduler they are dealing with to make
    sending decisions. Also, the paper presented a lot of
    results in table format, which made it very difficult
    to identify what was important. Graphs or statistics
    would have be more valuable.

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