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Dynamic Framed Slotted Aloha (DFSA) based tag
reading protocols rely on a tag estimation function to calculate
the best frame size to use for a given tag set. An inaccurate
estimate results in high identification delays and unnecessary
energy wastage. This is particularly serious when DFSA based
tag reading protocols are used in RFID-enhanced wireless sensor
networks (WSNs), where nodes are battery constrained. To this
end, this paper presents qualitative and quantitative analysis of
five tag estimation functions using Monte Carlo simulations. We
iteratively estimate a given set of tags and evaluate the mean
error, variability, skew and Kurtosis of each function’s error
distribution. Lastly, we compare and identify the most efficient
tag estimation function that is suitable for RFID-enhanced WSNs.
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