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Worst-case efficient external-memory priority queues [chapter]

Gerth Stølting Brodal, Jyrki Katajainen
1998 Lecture Notes in Computer Science  
. - Aggarwal, Vitter, 1988 Worst-Case Effeciency Internal Each priority queue operation should require (log 2 N ) External-Memory Priority Queues Binary heap - Williams, 1964 -Random memory accesses  ...  Incremental List Merging Lists Conclusion The first worst case external-memory priority-queue implementation. Open Problems Is the definition of "worst-case" reasonable in practice ?  ... 
doi:10.1007/bfb0054359 fatcat:pox4uo3nbnguhafaulzilf7o2q

Two new methods for constructing double-ended priority queues from priority queues

Amr Elmasry, Claus Jensen, Jyrki Katajainen
2008 Computing  
With the first transformation we obtain a double-ended priority queue which guarantees the worst-case cost of O(1) for find-min, find-max, insert, extract; and the worst-case cost of O(lg n) with at most  ...  With the second transformation we get a meldable double-ended priority queue which guarantees the worst-case cost of O(1) for find-min, find-max, insert, extract; the worst-case cost of O(lg n) with at  ...  Lemma 2 [13] There exists a meldable priority queue that supports find-min, insert, extract, and decrease at the worst-case cost of O (1) ; delete at the worst-case cost of O(lg n) including at most  ... 
doi:10.1007/s00607-008-0019-2 fatcat:tym6ges4yjgpzoa3a5wxtw5kdu

Fast Meldable Priority Queues

Gerth Stølting Brodal
1995 BRICS Report Series  
We present priority queues that support the operations MakeQueue,<br />FindMin, Insert and Meld in worst case time O(1) and Delete and<br />DeleteMin in worst case time O(log n).  ...  <br />To our knowledge this is the first priority queue implementation that<br />supports Meld in worst case constant time and DeleteMin in logarithmic<br />time.  ...  If we want to perform Insert in worst case constant time two efficient data structures exist. The implicit priority queues of Carlsson and Munro [2] and the relaxed heaps of Driscoll et al.  ... 
doi:10.7146/brics.v2i12.19515 fatcat:dxsmuwetabfvfebajaisjcfply

Fast meldable priority queues [chapter]

Gerth Stølting Brodal
1995 Lecture Notes in Computer Science  
We present priority queues that support the operations MakeQueue, FindMin, Insert and Meld in worst case time O(1) and Delete and DeleteMin in worst case time O(log n).  ...  The time bounds are optimal for all implementations where Meld takes worst case time o(n).  ...  If we want to perform Insert in worst case constant time two efficient data structures exist. The implicit priority queues of Carlsson and Munro [2] and the relaxed heaps of Driscoll et al.  ... 
doi:10.1007/3-540-60220-8_70 fatcat:iaau75pvyzhjrie2roitruncyi

Weak Heaps and Friends: Recent Developments [chapter]

Stefan Edelkamp, Amr Elmasry, Jyrki Katajainen, Armin Weiß
2013 Lecture Notes in Computer Science  
In applications where this set of operations is sufficient, the priority queue that the users would select is a binary heap [29] or a weak heap [7] .  ...  Weak Heaps In its elementary form, a priority queue is a data structure that stores a collection of elements and supports the operations construct, minimum, insert, and extract-min [4] .  ...  As a culmination, in [13] , an in-place priority queue was introduced that supports insert in O(1) worst-case time and extract-min in O(lg n) worst-case time involving at most lg n + O(1) element comparisons  ... 
doi:10.1007/978-3-642-45278-9_1 fatcat:xpymmd6toralpgl57qb3ia4ahm

Selectable Heaps and Optimal Lazy Search Trees [article]

Bryce Sandlund, Lingyi Zhang
2022 arXiv   pre-print
An O(1) time merge operation is also made possible when used as a priority queue, among other situations. If Brodal queues are used, all runtimes of the lazy search tree can be made worst-case.  ...  We show the O(log n) time extract minimum function of efficient priority queues can be generalized to the extraction of the k smallest elements in O(k log(n/k)) time (we define log(x) as max(log_2(x),  ...  Brodal gave two priority queues matching Fibonacci heap bounds but in the worst-case.  ... 
arXiv:2011.11772v3 fatcat:6rssj263o5c3fctwdhzftts2vq

Policy-Based Benchmarking of Weak Heaps and Their Relatives, [chapter]

Asger Bruun, Stefan Edelkamp, Jyrki Katajainen, Jens Rasmussen
2010 Lecture Notes in Computer Science  
In this paper we describe an experimental study where we evaluated the practical efficiency of three worst-case efficient priority queues: 1) a weak heap that is a binary tree fulfilling half-heap ordering  ...  A weak heap supports insert and decrease in logarithmic worst-case time, whereas a weak queue reduces the worst-case running time of insert to O(1), and a run-relaxed weak queue that of both insert and  ...  Hence, worst-case efficient priority queues should only be used in applications where worst-case efficiency is essential. 3) Memory management is expensive.  ... 
doi:10.1007/978-3-642-13193-6_36 fatcat:xbihqjez5zfcjopljjgtbk4egi

Improvements in double ended priority queues

M. Ziaur Rahman, Rezaul Alam Chowdhury, M. Kaykobad
2003 International Journal of Computer Mathematics  
We also show that in the worst case, this structure, though slightly costlier to create, is better than min-max heaps of Strothotte (Min-max Heaps and Generalized Priority Queues -CACM, 29(10), 996-1000  ...  Experimental results show that, in the average case, with the exception of creation phase data movement, our algorithm outperforms min-max heap of Strothotte in all other aspects.  ...  CONCLUDING REMARKS We have presented efficient algorithms for the implementation of implicit double-ended priority queues using min-max pair-heap.  ... 
doi:10.1080/207160310001599079 fatcat:3j3e5ohlwffqzblro7uoc3vshe

Multipartite priority queues

Amr Elmasry, Claus Jensen, Jyrki Katajainen
2008 ACM Transactions on Algorithms  
In particular, we give a priority queue which guarantees the worstcase cost of O(1) per minimum finding and insertion, and the worst-case cost of O(log n) with at most log n + O(1) element comparisons  ...  We introduce a framework for reducing the number of element comparisons performed in priority-queue operations.  ...  Deletion from the insert buffer is performed in the same way as that of the worst-case efficient binomial queue.  ... 
doi:10.1145/1435375.1435389 fatcat:7fvtifjtdvhqzm6ioudb7tolbe

Fat Heaps without Regular Counters [chapter]

Amr Elmasry, Jyrki Katajainen
2012 Lecture Notes in Computer Science  
Our variant is simpler to explain, more efficient, and easier to implement.  ...  We introduce a variant of fat heaps that does not rely on regular counters, and still achieves the optimal worst-case bounds: O(1) for find -min, insert and decrease, and O(lg n) for delete and delete-min  ...  Many data structures-such as worst-case-efficient finger trees [11] , fat heaps [12, 13] , fast meldable priority queues [1] , and worst-case-optimal meldable priority queues [2] -rely on numeral systems  ... 
doi:10.1007/978-3-642-28076-4_18 fatcat:vaf46pzhrvfcxocobeoy22cjzi

FAT HEAPS WITHOUT REGULAR COUNTERS

AMR ELMASRY, JYRKI KATAJAINEN
2013 Discrete Mathematics, Algorithms and Applications (DMAA)  
Our variant is simpler to explain, more efficient, and easier to implement.  ...  We introduce a variant of fat heaps that does not rely on regular counters, and still achieves the optimal worst-case bounds: O(1) for find -min, insert and decrease, and O(lg n) for delete and delete-min  ...  Many data structures-such as worst-case-efficient finger trees [11] , fat heaps [12, 13] , fast meldable priority queues [1] , and worst-case-optimal meldable priority queues [2] -rely on numeral systems  ... 
doi:10.1142/s1793830913600069 fatcat:gajg2zhz4fe6xc2yay5wxn6crq

An Efficient Construction Algorithm for a Class of Implicit Double-Ended Priority Queues

J. Chen
1995 Computer journal  
Priority queues and double-ended priority queues are fundamental data types in Computer Science, and various data structures have been proposed to implement them.  ...  In particular, diamond deques, interval heaps, min-max-pair heaps, and twin-heaps provide implicit structures for double-ended priority queues.  ...  Various data structures have been developed for implementing priority queues and priority deques efficiently.  ... 
doi:10.1093/comjnl/38.10.818 fatcat:snivpgidsng5tcclqrvuqlmppy

Hybrid LRU Algorithm for Enterprise Data Hub

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
This paper depicts about the experimental advantage of execution time optimization and efficient page/cache hit ratio, using hybrid Least Recently Used algorithm with priority mechanism.  ...  This research paper is to leverage the in memory processing for the business use case of Enterprise Data Hub.  ...  (Cache aware) O (log4 N) 2 Bottom up Binary Heap (worst case) O (log2 N) 3 Aligned 4-ary Heap (worst case) N:queue size, B: block size, M: cache size, l: (M), k: Pseudo code of LRU algorithm is represented  ... 
doi:10.35940/ijitee.l3489.119119 fatcat:l4so6pnmzfb5dac3ydgmych4g4

A comparative study of parallel and sequential priority queue algorithms

Robert Rönngren, Rassul Ayani
1997 ACM Transactions on Modeling and Computer Simulation  
For large queue sizes of 5,000 elements or more, the Calendar Queue and the Lazy Queue offer good average access times but have very long worst-case access times.  ...  The Skew Heap and the Splay Tree exhibit the best worst-case access times.  ...  Of the tested priority queues, the implicit binary heap had the best worst-case performance for individual operations, which was better than O(n).  ... 
doi:10.1145/249204.249205 fatcat:iglffwap4vebrgerxu2iucsfk4

Multiresolution Priority Queues [article]

Jordi Ros-Giralt, Alan Commike, Peter Cullen, Jeff Lucovsky, Dilip Madathil, Richard Lethin
2017 arXiv   pre-print
The new data structure can reduce the worst case performance of inserting an element from O(log(n)) to O(log(r)), where n is the number of elements in the queue and r is the number of resolution groups  ...  Priority queues are container data structures essential to many high performance computing (HPC) applications.  ...  Williams' work lead to a very efficient implementation with a worst case cost to insert and extract elements from the priority queue of , (log(n)) O where is the number of elements in the queue.  ... 
arXiv:1705.09642v6 fatcat:3y4jelk7wzeepflwrlttddhue4
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