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Advanced Data Structures: Priority Queue and Binary Heap Overview

Learn about priority queues, binary heaps, and their operations in this comprehensive overview for the CS223 Advanced Data Structures and Algorithms class. Explore possible solutions, binary tree concepts, heap insertion and deletion, and applications like finding the kth smallest or largest element. Understand time complexities and the buildHeap algorithm.

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Advanced Data Structures: Priority Queue and Binary Heap Overview

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  1. Priority Queue and Binary HeapNeil Tang02/12/2008 CS223 Advanced Data Structures and Algorithms

  2. Class Overview • Priority queue • Binary heap • Heap operations: insert, deleteMin, de/increaseKey, delete, buildHeap • Application CS223 Advanced Data Structures and Algorithms

  3. Priority Queue A priority queue is a queue in which each element has a priority and elements with higher priorities are supposed to be removed before the elements with lower priorities. CS223 Advanced Data Structures and Algorithms

  4. Possible Solutions • Linked list: Insert at the front (O(1)) and traverse the list to delete (O(N)). • Linked list: Keep it always sorted.traverse the list to insert (O(N)) and delete the first element (O(1)). • Binary search tree CS223 Advanced Data Structures and Algorithms

  5. Binary Heap A binary heap is a binary tree that is completely filled, with possible exception of the bottom level and in which for every node X, the key in the parent of X is smaller than (or equal to) the key in X. CS223 Advanced Data Structures and Algorithms

  6. Binary Heap • A complete binary tree of height h has between 2h and 2h+1 -1 nodes. So h = logN. • For any element in array position i, its left child in position 2i and the right child is in position (2i+1), and the parent is in i/2. CS223 Advanced Data Structures and Algorithms

  7. Insert 14 CS223 Advanced Data Structures and Algorithms

  8. Insert (Percolate Up) Time complexity: O(logN) CS223 Advanced Data Structures and Algorithms

  9. deleteMin CS223 Advanced Data Structures and Algorithms

  10. deleteMin (Percolate Down) Time complexity: O(logN) CS223 Advanced Data Structures and Algorithms

  11. Other Operations • decreaseKey(p,) • increaseKey(p, ) • delete(p)? • delete(p)=decreaseKey(p,)+deleteMin() CS223 Advanced Data Structures and Algorithms

  12. buildHeap CS223 Advanced Data Structures and Algorithms

  13. buildHeap CS223 Advanced Data Structures and Algorithms

  14. buildHeap CS223 Advanced Data Structures and Algorithms

  15. buildHeap • Theorem: For the perfect binary tree of height 2h+1-1 nodes the sum of the heights of the nodes is 2h+1-1-(h+1). • Time complexity: 2*(2h+1-1-(h+1)) = O(N). CS223 Advanced Data Structures and Algorithms

  16. Applications • Problem: find the kth smallest element. • Algorithm: buildHeap, then deleteMin k times. • Time complexity: O(N+klogN) = O(NlogN). CS223 Advanced Data Structures and Algorithms

  17. Applications • Problem: find the kth largest element. • Algorithm: buildHeap with the first k elements, check the rest one by one. In each step, if the new element is larger, deleteMin and insert the new one. • Time complexity: O(k+(N-k)logk) = O(NlogN). CS223 Advanced Data Structures and Algorithms

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