  This study introduces time-windowed variations of three established
trajectory simplification algorithms. These new algorithms are specifically
designed to be used in contexts with bandwidth limitations. We present the
details of these algorithms and highlight the differences compared to their
classical counterparts.
  To evaluate their performance, we conduct accuracy assessments for varying
sizes of time windows, utilizing two different datasets and exploring different
compression ratios. The accuracies of the proposed algorithms are compared with
those of existing methods. Our findings demonstrate that, for larger time
windows, the enhanced version of the bandwidth-constrained STTrace outperforms
other algorithms, with the bandwidth-constrained improved version of \squish
also yielding satisfactory results at a lower computational cost. Conversely,
for short time windows, only the bandwidth-constrained version of Dead
Reckoning remains satisfactory.
