Found 345 Articles for Data Structure Algorithms

Dynamic Finger Search Trees in Data Structure

Arnab Chakraborty
Updated on 07-Jan-2020 11:29:21

256 Views

A dynamic finger search data structure should in addition to finger searches also perform the insertion and deletion of elements at a position given by a finger.Finger search trees is defined as a variant of B-trees supporting finger searches in O(log d) time and updates in O(1) time, assuming that only O(1) moveable fingers are maintained.Traversing a finger d positions requires O(log d) time.The finger search trees (that means AVL-trees, red-black trees) constructions either consider a fixed constant number of fingers or only support updates in amortized constant time.Constructions supporting an arbitrary number of fingers and with worst case update ... Read More

Finger Searching in Data Structure

Arnab Chakraborty
Updated on 07-Jan-2020 09:42:30

261 Views

A finger search on a data structure is defined as an extension of any search operation that structure supports, where a reference (finger) to an element in the data structure is given along with the query. While the search time for an element is most frequently denoted as a function of the number of elements in a data structure, finger search times are treated as a function of the distance between the element and the finger.In a set of m elements, the distance d(a, b) between two elements a and b is their difference in rank. If elements a and ... Read More

Multi-Way Trees

Arnab Chakraborty
Updated on 03-Jan-2020 06:14:24

13K+ Views

A multiway tree is defined as a tree that can have more than two children. If a multiway tree can have maximum m children, then this tree is called as multiway tree of order m (or an m-way tree).As with the other trees that have been studied, the nodes in an m-way tree will be made up of m-1 key fields and pointers to children.multiway tree of order 5To make the processing of m-way trees easier some type of constraint or order will be imposed on the keys within each node, resulting in a multiway search tree of order m ... Read More

Multidimensional Binary Search Trees

Arnab Chakraborty
Updated on 03-Jan-2020 06:10:57

1K+ Views

Basic conceptThe multidimensional binary search tree (abbreviated k-d tree) is defined as a data structure for storing multikey records. This structure has been implemented to solve a number of "geometric" problems in statistics and data analysis.A k-d tree (short for k-dimensional tree) is defined as a space-partitioning data structure for organizing points in a k-dimensional space. Data structure k-d trees are implemented for several applications, for example, searches involving a multidimensional search key (e.g. range searches and nearest neighbor searches). k-d trees are treated as a special case of binary space partitioning trees.Informal descriptionThe k-d tree is a binary tree ... Read More

Rebalancing Algorithms

Arnab Chakraborty
Updated on 03-Jan-2020 06:00:47

567 Views

The rebalancing Algorithms can be performed in following way −Day-Stout-Warren AlgorithmWe can implement actually rebalance method using the Day-Stout-Warren Algorithm.It's linear in the number of nodes.The following is a presentation of the basic DSW Algorithm in pseudo code.A node is allocated called as the "pseudo-root" and make the tree's actual root as the right child of the pseudo-root.Call tree-to-vine function for converting tree to sorted linked list with the pseudo-root as its argument.Call vine-to-tree function for converting sorted linked list to tree again with the pseudo-root and the size (number of elements) of the tree as its argument.The tree's actual ... Read More

Blocked Bloom Filter

Arnab Chakraborty
Updated on 03-Jan-2020 05:59:33

647 Views

We select a memory block first.Then we select local Bloom Filter within each block.It might cause imbalance between memory blocksThis filter is efficient, but poor false positive rate(FPR).At first instance, blocked Bloom filters should have the same FPR (False Positive Rate) as standard Bloom filters of the same size.Blocked Bloom Filter consists of a sequence of block b comparatively less than standard Bloom filters (Bloom filter blocks), each of which fits into one cache-line.Blocked Bloom filter scheme is differentiated from the partition schemes, where each bit is inserted into a different block.Blocked Bloom Filter is implemented in following ways −Bit ... Read More

Counter Size and Counter Overflow

Arnab Chakraborty
Updated on 03-Jan-2020 05:58:21

538 Views

Counter SizeWe must select counters large enough for avoiding overflow.Size is 4 bits/counter suggested by Poisson approximation.Average load implementing k = (ln 2)m/n counters is ln 2.Probability a counter has load minimum 16:≈e-ln2(ln 2)16/16!≈6.78E-17We consider 4 bits/counter for comparisons.Counter OverflowWhen a counter does overflow, it may be arrived at its maximum value.This situation can later cause a false negative only if eventually the counter goes down to 0 when it should have remained at nonzero.The expected time to this situation is very large but is something we need to keep in mind for any application that does not permit false ... Read More

Counting Bloom Filter

Arnab Chakraborty
Updated on 03-Jan-2020 05:56:52

405 Views

Basic ConceptA Counting Bloom filter is defined as a generalized data structure of Bloom filter that is implemented to test whether a count number of a given element is less than a given threshold when a sequence of elements is given. As a generalized form, of Bloom filter there is possibility of false positive matches, but no chance of false negatives – in other words, a query returns either "possibly higher or equal than the threshold" or "definitely less than the threshold".Algorithm descriptionMost of the parameters, used under counting bloom filter, are defined same with Bloom filter, such as n, ... Read More

Performance Metrics

Arnab Chakraborty
Updated on 03-Jan-2020 05:55:55

237 Views

There are three performance metrics for Bloom filters that can be traded off: computation or execution time (corresponds to the number k of hash functions), size of filter (corresponds to the number m of bits), and probability of error (corresponds to the false positive ratef = (1 − p)k )The Bloom filter (BF) introduces an error tolerance to enhance lookup performance and space efficiency. The Bloom filter either returns true or false. Thus, the result of Bloom filter is fallen under any one of the following classes: true positive, false positive, true negative, and false negative. Maximum number the Bloom ... Read More

Bloom Filter

Arnab Chakraborty
Updated on 03-Jan-2020 05:54:34

3K+ Views

A Bloom filter is defined as a data structure designed to identify of a element’s presence in a set in a rapid and memory efficient manner.A specific data structure named as probabilistic data structure is implemented as bloom filter. This data structure helps us to identify that an element is either present or absent in a set.Bit Vector is implemented as a base data structure. Here's a small one we'll use to explain123456789101112131415Each empty cell in that table specifies a bit and the number below it its index or position. To append an element to the Bloom filter, we simply hash ... Read More

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