CITS3002 Computer Networks - Labsheet 3  
 

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Look after yourself!

Labsheet 3 - sample solutions and discussion

  1. ....
    For this task, using the cnet network simulator:

    • Add piggybacking to the standard stop-and-wait protocol.
    • Modify the topology file, changing the attributes of message delivery, bandwidth, frame corruption and loss, to determine under which conditions piggybacking offers an advantage....

  2. ....
    To perform a valid scientific experiment (which, after all, is what we're doing), we need to hold all conditions/arrtibutes constant and vary just one over time, perform the same experiment for both the stop-and-wait and piggybacking protocols.

    As in Labsheet 2, develop a plot to help you to visually compare the results of your experiment....

    The coded solution in stopandwait-vs-piggyback.zip show that, under identical conditions of frame corruption and loss, piggybacking transmits more (but a similar number of) frames, delivers more (but a similar number of) messages, and provides a lower average delivery time per message:

    Why?



  3. ....
    The simplest variant of a sliding-window protocol is termed the go-back-N protocol, in which the receiver simply discards (ignores) all frames after a bad one. This corresponds to a receiver window size of 1.

    After it learns of a lost (or corrupted frame), the sender retransmits all unacknowledged frames - it "goes back N frames" and starts again. Notice that in the presence of significant errors that bandwidth is wasted because the receiver only 'buffers' a single frame.

    Following the same experimental approach as in the first task, use cnet to implement the go-back-N protocol, and determine under which conditions it is an improvement over the stop-and-wait protocol.

    The coded solution in stopandwait-vs-gobackn.zip show that, under identical conditions of frame corruption and loss, the go-back-N sliding-window protocol transmits (significantly) more frames, delivers (significantly) more messages, but provides a higher average delivery time per message:

    Why?



Chris McDonald

March 2024.

The University of Western Australia

Computer Science and Software Engineering

CRICOS Code: 00126G
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