Making Data Structures Confluently Persistent
... Figure 1: A version tree of a fully persistent data structure. The underlying data structure is trivial and consists of one node with two fields x and y. Driscoll, Sleator, and Tarjan [10] coined the term confluently persistent for fully persistent structures that support such meld operations. Much ...
... Figure 1: A version tree of a fully persistent data structure. The underlying data structure is trivial and consists of one node with two fields x and y. Driscoll, Sleator, and Tarjan [10] coined the term confluently persistent for fully persistent structures that support such meld operations. Much ...
Heaps and heapsort on secondary storage
... The external costs are measured in terms of page transfers (reads and writes). The complexity will be determined only for an intermixed sequence of insert and deletemax operations - the worst case of a single operation can be really bad; for example in delete-max, the refilling may propagate to all ...
... The external costs are measured in terms of page transfers (reads and writes). The complexity will be determined only for an intermixed sequence of insert and deletemax operations - the worst case of a single operation can be really bad; for example in delete-max, the refilling may propagate to all ...
Chapter14. Tournament Trees
... Definition: A winner tree for n players is a complete binary tree with n external and n-1 internal nodes Each internal node records the winner of the match played there. ...
... Definition: A winner tree for n players is a complete binary tree with n external and n-1 internal nodes Each internal node records the winner of the match played there. ...
Optimal Purely Functional Priority Queues
... addition also applies to melding two queues. We step through the trees of both queues in increasing order of rank, linking trees of equal rank as we go. Once again, each link corresponds to a carry. This also requires O(log n) time. The trickiest operation is deleteMin. We first find the tree with t ...
... addition also applies to melding two queues. We step through the trees of both queues in increasing order of rank, linking trees of equal rank as we go. Once again, each link corresponds to a carry. This also requires O(log n) time. The trickiest operation is deleteMin. We first find the tree with t ...
Dynamic Ham-Sandwich Cuts in the Plane
... there is one convex point set (or equivalently, one convex polygon) of each color, so k = 2. Another case of interest is when P1 , P2 , . . . , Pk form nested convex point sets. In this case, we obtain the convex-hull peeling layers or onion peeling [Bar76, Edd82] of the points P1 ∪ P2 ∪ · · · Pk . ...
... there is one convex point set (or equivalently, one convex polygon) of each color, so k = 2. Another case of interest is when P1 , P2 , . . . , Pk form nested convex point sets. In this case, we obtain the convex-hull peeling layers or onion peeling [Bar76, Edd82] of the points P1 ∪ P2 ∪ · · · Pk . ...
Eindhoven University of Technology MASTER An experimental
... I am very grateful to dr. Herman Haverkort, my advisor, for all the support and help during this thesis. This work would not have been completed in time without the numerous discussions with him. I am also indebted to him for spending the huge e ort reviewing the early versions of this document, in ...
... I am very grateful to dr. Herman Haverkort, my advisor, for all the support and help during this thesis. This work would not have been completed in time without the numerous discussions with him. I am also indebted to him for spending the huge e ort reviewing the early versions of this document, in ...
ppt
... Updating Left (right) Slab Structures • Recall that each internal node augmented with minimal left xcoordinate segment below each child • Insert: – Insert in leaf l and (B-tree) rebalance – Insert segment in relevant nodes on root-l path • Delete: – Delete from leaf l and rebalance as in B-tree – Fi ...
... Updating Left (right) Slab Structures • Recall that each internal node augmented with minimal left xcoordinate segment below each child • Insert: – Insert in leaf l and (B-tree) rebalance – Insert segment in relevant nodes on root-l path • Delete: – Delete from leaf l and rebalance as in B-tree – Fi ...
Simulated Pointers
... What if we want to have linked structures on disk User-defined pointers instead of Java references ...
... What if we want to have linked structures on disk User-defined pointers instead of Java references ...
On the Fast Construction of Spatial Hierarchies for Ray Tracing
... In this paper we focus on SKD-trees described in Section 4.1. Obviously, for SKD-trees we could use the spatial median strategy similar to other data structures [14, 33, 44]. However, it has been shown on kd-trees that spatial median results in an inferior performance of ray tracing for skewed distr ...
... In this paper we focus on SKD-trees described in Section 4.1. Obviously, for SKD-trees we could use the spatial median strategy similar to other data structures [14, 33, 44]. However, it has been shown on kd-trees that spatial median results in an inferior performance of ray tracing for skewed distr ...
Concurrent Data Structures (Book Chapter).
... It requires a known bound P on the number of threads that access the counter, and it requires O(P ) space. While it provides better throughout under heavy loads, that is, when accessed by many concurrent threads, its best-case performance under low loads is poor: It must still traverse O(log P ) nod ...
... It requires a known bound P on the number of threads that access the counter, and it requires O(P ) space. While it provides better throughout under heavy loads, that is, when accessed by many concurrent threads, its best-case performance under low loads is poor: It must still traverse O(log P ) nod ...
Concise Notes on Data Structures and Algorithms
... Concise Notes on Data Structures and Algorithms Ruby Edition Christopher Fox ...
... Concise Notes on Data Structures and Algorithms Ruby Edition Christopher Fox ...
Energy Efficient In-Network Data Indexing for Mobile Wireless
... 1(a), a sensed field with randomly deployed sensor nodes is shown. Part (b) of the same figure shows the nodes location distribution, after the occurrence of an event of interest in the southeast corner of the field, where the application or mobility control algorithm (as [29]) has steered more sens ...
... 1(a), a sensed field with randomly deployed sensor nodes is shown. Part (b) of the same figure shows the nodes location distribution, after the occurrence of an event of interest in the southeast corner of the field, where the application or mobility control algorithm (as [29]) has steered more sens ...
Isosurface Extraction and Spatial Filtering Using Persistent Octree (POT) Member, IEEE
... active cells it stores and so is the time it takes to traverse the tree to report these active cells. Furthermore, we can show that the compact octree requires only an amortized constant number of node changes for each insertion or deletion when applied to our particular problem (see Section 4.1 of ...
... active cells it stores and so is the time it takes to traverse the tree to report these active cells. Furthermore, we can show that the compact octree requires only an amortized constant number of node changes for each insertion or deletion when applied to our particular problem (see Section 4.1 of ...
Index Tuning
... balanced B+-tree as records are inserted – Off-line: inserted/deleted records are inserted in a specific data structure and indexes are modified offline (when the DBA requests it, regularly or when some condition is met). • Log-Structured Merge (LSM)-tree: Records inserted in RAM (C0-tree not necess ...
... balanced B+-tree as records are inserted – Off-line: inserted/deleted records are inserted in a specific data structure and indexes are modified offline (when the DBA requests it, regularly or when some condition is met). • Log-Structured Merge (LSM)-tree: Records inserted in RAM (C0-tree not necess ...
The Union of Probabilistic Boxes: Maintaining the Volume
... time O(nd/2 2O(log n) ). Despite a long and distinguished history, the computational complexity of the problem has remained largely unresolved for d ≥ 3 since the breakthrough result of Overmars and Yap [13], with time complexity O(nd/2 log n). Most of the work in the past several years has focused ...
... time O(nd/2 2O(log n) ). Despite a long and distinguished history, the computational complexity of the problem has remained largely unresolved for d ≥ 3 since the breakthrough result of Overmars and Yap [13], with time complexity O(nd/2 log n). Most of the work in the past several years has focused ...
ADT Dictionaries and Hashing
... – Small enough to avoid wasting space. – Large enough to avoid many collisions and keep linked-lists short. – Typically 1/5 or 1/10 of the total number of elements. ...
... – Small enough to avoid wasting space. – Large enough to avoid many collisions and keep linked-lists short. – Typically 1/5 or 1/10 of the total number of elements. ...
Binary search tree
In computer science, binary search trees (BST), sometimes called ordered or sorted binary trees, are a particular type of containers: data structures that store ""items"" (such as numbers, names and etc.) in memory. They allow fast lookup, addition and removal of items, and can be used to implement either dynamic sets of items, or lookup tables that allow finding an item by its key (e.g., finding the phone number of a person by name).Binary search trees keep their keys in sorted order, so that lookup and other operations can use the principle of binary search: when looking for a key in a tree (or a place to insert a new key), they traverse the tree from root to leaf, making comparisons to keys stored in the nodes of the tree and deciding, based on the comparison, to continue searching in the left or right subtrees. On average, this means that each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree. This is much better than the linear time required to find items by key in an (unsorted) array, but slower than the corresponding operations on hash tables.They are a special case of the more general B-tree with order equal to two.