- On the List Update Problem with Advice.
- Joan Boyar, Shahin Kamali, Kim S. Larsen, and Alejandro López-Ortiz.
Information and Computation, 253(3): 411-423, 2017.
We study the online list update problem under the advice model of
computation. Under this model, an online algorithm receives partial
information about the unknown parts of the input in the form of some
bits of advice generated by a benevolent offline oracle. We show that
advice of linear size is required and sufficient for a deterministic
algorithm to achieve an optimal solution or even a competitive ratio
better than 15/14
. On the other hand, we show that surprisingly two
bits of advice are sufficient to break the lower bound of 2
the competitive ratio of deterministic online algorithms and achieve a
deterministic algorithm with a competitive ratio of
this upper-bound argument, the bits of advice determine the algorithm
with smaller cost among three classical online algorithms, Timestamp and two
members of the MoveToFrontTwo family of algorithms.
We also show that MoveToFrontTwo algorithms are 2.5
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