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Why Some Heaps Support Constant-Amortized-Time Decrease-Key Operations, and Others Do Not

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Automata, Languages, and Programming (ICALP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8572))

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Abstract

A lower bound is presented which shows that a class of heap algorithms in the pointer model with only heap pointers must spend \(\Omega \left( \frac{\log \log n}{\log \log \log n} \right)\) amortized time on the Decrease-Key operation (given O(logn) amortized-time Extract-Min). Intuitively, this bound shows the key to having O(1)-time Decrease-Key is the ability to sort O(logn) items in O(logn) time; Fibonacci heaps [M. .L. Fredman and R. E. Tarjan. J. ACM 34(3):596-615 (1987)] do this through the use of bucket sort. Our lower bound also holds no matter how much data is augmented; this is in contrast to the lower bound of Fredman [J. ACM 46(4):473-501 (1999)] who showed a tradeoff between the number of augmented bits and the amortized cost of Decrease-Key. A new heap data structure, the sort heap, is presented. This heap is a simplification of the heap of Elmasry [SODA 2009: 471-476] and shares with it a O(loglogn) amortized-time Decrease-Key, but with a straightforward implementation such that our lower bound holds. Thus a natural model is presented for a pointer-based heap such that the amortized runtime of a self-adjusting structure and amortized lower asymptotic bounds for Decrease-Key differ by but a O(logloglogn) factor.

The full version is on the arXiv at CoRR abs/1302.6641 (2013).

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Iacono, J., Özkan, Ö. (2014). Why Some Heaps Support Constant-Amortized-Time Decrease-Key Operations, and Others Do Not. In: Esparza, J., Fraigniaud, P., Husfeldt, T., Koutsoupias, E. (eds) Automata, Languages, and Programming. ICALP 2014. Lecture Notes in Computer Science, vol 8572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43948-7_53

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  • DOI: https://doi.org/10.1007/978-3-662-43948-7_53

  • Publisher Name: Springer, Berlin, Heidelberg

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