  The bin covering problem asks for covering a maximum number of bins with an
online sequence of $n$ items of different sizes in the range $(0,1]$; a bin is
said to be covered if it receives items of total size at least 1. We study this
problem in the advice setting and provide tight bounds for the size of advice
required to achieve optimal solutions. Moreover, we show that any algorithm
with advice of size $o(\log \log n)$ has a competitive ratio of at most 0.5. In
other words, advice of size $o(\log \log n)$ is useless for improving the
competitive ratio of 0.5, attainable by an online algorithm without advice.
This result highlights a difference between the bin covering and the bin
packing problems in the advice model: for the bin packing problem, there are
several algorithms with advice of constant size that outperform online
algorithms without advice. Furthermore, we show that advice of size $O(\log
\log n)$ is sufficient to achieve a competitive ratio that is arbitrarily close
to $0.53\bar{3}$ and hence strictly better than the best ratio $0.5$ attainable
by purely online algorithms. The technicalities involved in introducing and
analyzing this algorithm are quite different from the existing results for the
bin packing problem and confirm the different nature of these two problems.
Finally, we show that a linear number of bits of advice is necessary to achieve
any competitive ratio better than 15/16 for the online bin covering problem.
