Probabilistic Data Structures for Priority Queues

We present several simple probabilistic data structures for implementing priority queues. We present a data structure called simple bottom-up sampled heap (SBSH), supporting insert in O(1) expected time and delete, delete minimum, decrease key and meld in O(log n) time with high probability. An extension of SBSH called BSH1, supporting insert and meld in O(1) worst case time is presented. This data structure uses a novel “buffering technique” to improve the expected bounds to worst-case bounds. Another extension of SBSH called BSH2, performing insert, decrease key and meld in O(1) amortized expected time and delete and delete minimum in O(log n) time with high probability is also presented. The amortized performance of this data structure is comparable to that of Fibonacci heaps (in probabilistic terms). Moreover, unlike Fibonacci heaps, each operation takes O(log n) time with high probability, making the data structure suitable for real-time applications.