By Kurt Mehlhorn (auth.), Sudebkumar Prasant Pal, Kunihiko Sadakane (eds.)

ISBN-10: 331904656X

ISBN-13: 9783319046563

ISBN-10: 3319046578

ISBN-13: 9783319046570

This publication constitutes the revised chosen papers of the eighth overseas Workshop on Algorithms and Computation, WALCOM 2014, held in Chennai, India, in February 2014. The 29 complete papers offered including three invited talks have been conscientiously reviewed and chosen from sixty two submissions. The papers are geared up in topical sections on computational geometry, algorithms and approximations, disbursed computing and networks, graph algorithms, complexity and limits, and graph embeddings and drawings.

**Read or Download Algorithms and Computation: 8th International Workshop, WALCOM 2014, Chennai, India, February 13-15, 2014, Proceedings PDF**

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**Extra resources for Algorithms and Computation: 8th International Workshop, WALCOM 2014, Chennai, India, February 13-15, 2014, Proceedings**

**Sample text**

F (pi ) → f (pj ) The basic idea of our algorithm is as follows: we test the points of Lq in order until we find the first k skyline points and store them in Sk . To be specific, for a point p, we perform the dominance test only with points currently stored in Sk . So if p is not dominated by any point of Sk , we insert p to Sk and update Vk = maxs≤Sk f (s). After finding first k skyline points, we only consider points p ≥ Lq that satisfy f (p) < Vk , as we already have k skyline points that have a better score than p.

All queries studied in the following sections are orthogonal and axis-parallel, unless explicitly speciﬁed otherwise. All results are in the pointer machine model. 1 Generalized Reporting in One Dimension Given a set of points in one dimension where each point has a color (not necessarily unique) associated with it, we want to preprocess the point-set such that given a query range we can eﬃciently report the distinct colors in that range. Gupta et al. [11] showed a transformation which reduces the generalized one dimensional range reporting problem into the standard grounded range reporting problem in two dimensions and solved the problem using a priority search tree (PST) [17].

The preprocessing stage involves: 38 N. Moidu et al. 1. The building of the tree Tx , which is a one dimensional range tree. It takes O(n) space and can be built in O(n log n) time. 2. The building of the tree T , which takes O(n log n) time. The number of nodes in T is the same as the number of points in P , therefore T has size O(n). 1. If the length of a heavy path is lh , it takes O(lh ) space and O(lh log lh ) time to build the required data structure. Clearly the overall space requirement is O(n) while the time required is O(n log n).

### Algorithms and Computation: 8th International Workshop, WALCOM 2014, Chennai, India, February 13-15, 2014, Proceedings by Kurt Mehlhorn (auth.), Sudebkumar Prasant Pal, Kunihiko Sadakane (eds.)

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