On the List Update Problem with Advice

Joan Boyar, Shahin Kamali, Kim Skak Larsen, Alejandro López-Ortiz

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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 is sufficient to break the lower bound of 2 on the competitive ratio of deterministic online algorithms and achieve a deterministic algorithm with a competitive ratio of 1.6¯ . In this upper-bound argument, the bits of advice determine the algorithm with smaller cost among three classical online algorithms.
Original languageEnglish
Title of host publicationLanguage and Automata Theory and Applications : 8th International Conference, LATA 2014, Madrid, Spain, March 10-14, 2014. Proceedings
EditorsAdrian-Horia Dediu et al.
Publication date2014
ISBN (Print)978-3-319-04920-5
ISBN (Electronic)978-3-319-04921-2
Publication statusPublished - 2014
Event8th International Conference on Language and Automata Theory and Applications - Madrid, Spain
Duration: 10. Mar 201414. Mar 2014
Conference number: 8


Conference8th International Conference on Language and Automata Theory and Applications
SeriesLecture Notes in Computer Science


Dive into the research topics of 'On the List Update Problem with Advice'. Together they form a unique fingerprint.

Cite this