Binary Search Trees of Almost Optimal Height

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Binary Search Trees of Almost Optimal Height

  1. 1. simone tino Algorithms & Complexity evaluation Discoverying Binary Search Trees of Almost Optimal Height @ Università di Catania #20/11/2012
  2. 2. so... what’s this all about? Introducing SBB(k) trees Before getting to SBB(k) trees, we really have a long way to go... What about a shortcut? AVL-Tree (a,b)-Tree SBB(k) Tree Binary Search Tree B-Tree SBB Tree SBB-tree and SBB(k)-tree introduce the concept of “pseudo-node”! Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  3. 3. some definitions... Matrioska-like definitions, let’s start from the most inner one... Optimally balanced The difference between its maximum and minimum heights <= 1 Introducing important concepts: Pseudo-Node Minimum height Maximum height Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  4. 4. Let’s open the box and see what’s inside... Defining SBB(k)-trees SBB(k)-tree is a binary-tree which satisfies the following 3 criteria... The Pseudo-Root is optimally balanced and has a maximum height <= (k+1). All other Pseudo-Nodes have a minimum height >= (k) and a maximum height <= (k+1). The number of Pseudo-Nodes on the path from the root to a leaf is the same for all leaves. Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  5. 5. 47 The importance of k Let’s draw some trees... 35 64 19 9 50 40 28 38 44 48 69 52 66 77 47 35 64 40 k -> k++ 19 9 38 28 44 50 48 69 52 66 77 What happens when k increases? Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  6. 6. Caging SBB(k)-trees? Height upper-bound START h ( ab-tree ) 1+ log a h ( SBB(k)-tree ) n +1 2 = 1+ log ( n + 1) 1 log ( 2 k ) log ( n + 1) + h ( ab-tree ) log ( n + 1) + 1+ 1+ 1 k log ( n + 1) 1 log ( 2 k ) log ( n + 1) + 1 1 k h ( SBB(k)-tree ) 1 1+ k log ( n + 1) Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  7. 7. Maintenance algorithms ops.balance ops.coBalance Merging, cutting, rotating... the bricks of SBB(k)-trees ops.split ops.join Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  8. 8. Update algorithms ops.insertion Inserting a node in the tree. Analyzing algorithms for insertion and deletion in SBB(k)-trees int ops.insertion(pn P, int c) { return (c==0) ? ops.balance(P,null) : /*(c==1)*/ ops.split(P,null); } ops.deletion Deleting a node in the tree. int ops.deletion(pn P, pn S, int c) { return (c==0x00) ? ops.balance(P,S) : ops.rotation() + (c==0x10) ? ops.coBalance(P,S) : /*(c==0x11)*/ ops.join(P,S); } Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  9. 9. Inspecting ops.balance and most important issues Restructuring Work A very important operation is Restructuring. It is needed to keep the tree a SBB(k)-tree. Restructuring is performed by the Balance operation. Restructuring Work = ops.balance insertion 2 k+2 2P max ( ll ( P ) ,rl ( P )) log ( P + 1) 2k 4 deletion 3 2 k+1 2k 7 Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  10. 10. Binding k to n and seeing what happens Improving height log log ( n + 1) log log ( 3n ) k Recalling dynamic arrays, we can create a range for k At the begging, we proved the upper-bound. By tuning k, we improve the upper-bound h ( SBB(k)-tree ) k = O ( log log n ) O ( log n ) 1+ 1 k 1+ 1 log log ( n + 1) log ( n + 1) log ( n + 1) ( ) O 2 k Restructuring work Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  11. 11. An efficient application What’s this? Am I seeing double ?!? Keeping two SBB(k)-trees synchronized Ghosting one tree on the other one Hiding rebuilding work Presentation by Simone Tino - All rights reserved. Authored from October 2012 to November 2012 - University of Catania - Faculty of Computer Science - Algoritmi e Complessità
  12. 12. the end thank you by simone tino

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