This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: 6.851: Advanced Data Structures Spring 2010 Lecture 10 March 8, 2010 Prof. Erik Demaine 1 Overview In the last lecture we covered van Emde Boas and yfast trees, integer data structures which support insert, delete, predecessor, and successor operations in log( w ) time. These data structures are based on the Word RAM model, where we can manipulate a constant number of wbit words in constant time. In this lecture we covered fusion trees, as described by Fredman and Willard [1]. A fusion tree is a static data structure storing n wbit integers which supports predecessor and successor queries in O (log w n ) time per query and O ( n ) space. There is also a dynamic version of fusion trees which get O ( log w ( n ) + log ( log ( n ))) for updates, as described by Andersson and Thorup [2], but we did not cover this. Depending on whether n is small or large compared to w , we can use fusion trees or log n van Emde Boas trees, and our query time will be O (min log w , log w ). This minimum will never be greater than O ( log n ), giving us a better than logarithmic bound which only depends on n . 2 Fusion Trees A fusion tree is a Btree with a branching factor of w 1 / 5 . The depth of such a tree is log w 1 / 5 ( n ) = log( n ) / log( w 1 / 5 ) = 5 log( n ) / log( w ). In order to actually achieve O (log( n ) / log( w )) time for queries, we must deal with each node we encounter in constant time. However, there are w 1 / 5 keys, each w bits long, in each node: in constant time, we can only do a constant number of operations on a constant number of wbit words. To solve this problem, we will only compare the interesting bits of the keys. 2.1 Interesting bits Consider what a trie containing the keys would look like. This trie would have height w , the length of the keys, and would have k = O ( w 1 / 5 ) leaves (since the keys are distinct). Interesting bits are bits which correspond to levels in this trie with branching nodesthese are the bits we will look at in order to distinguish keys. Since our trie has k leaves, it has k 1 branching nodes, and at most k 1 interesting bits (since multiple branching nodes might be on the same level). We will call the indices of the interesting bits b through b r 1 ....
View
Full
Document
This note was uploaded on 03/31/2011 for the course EECS 6.851 taught by Professor Erikdemaine during the Spring '10 term at MIT.
 Spring '10
 ErikDemaine
 Data Structures

Click to edit the document details