Priority Queues Resilient to Memory Faults

Jørgensen, Allan Grønlund; Moruz, Gabriel; Mølhave, Thomas

doi:10.1007/978-3-540-73951-7_12

Cited by 32 publications

(34 citation statements)

References 20 publications

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“…Thus, their priority queue matches the performance of classical optimal priority queues in the RAM model when the number of corruptions tolerated is O(log n). An essentially matching lower bound is also proved in [19]: a resilient priority queue containing n elements, with n > δ, must use Ω(log n + δ) comparisons to answer an insert followed by a deletemin.…”

Section: Discussionmentioning

confidence: 97%

“…After this work, optimal resilient dictionaries and resilient priority queues were presented in [8] and [19], respectively. The dictionary designed in [8] requires linear space, and supports each operation in O(log n + δ) amortized worst-case time.…”

Section: Discussionmentioning

confidence: 99%

“…A resilient priority queue maintains a set of elements under the operations insert and deletemin: insert adds an element and deletemin deletes and returns either the minimum uncorrupted value or a corrupted value. In [19], Jorgensen et al show how to support both insert and deletemin operations in O(log n+δ) amortized time per operation. Thus, their priority queue matches the performance of classical optimal priority queues in the RAM model when the number of corruptions tolerated is O(log n).…”

Section: Discussionmentioning

confidence: 99%

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Resilient dictionaries

Finocchi

Grandoni

Italiano

2009

ACM Trans. Algorithms

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We address the problem of designing data structures in the presence of faults that may arbitrarily corrupt memory locations. More precisely, we assume that an adaptive adversary can arbitrarily overwrite the content of up to δ memory locations, that corrupted locations cannot be detected, and that only O(1) memory locations are safe. In this framework, we call a data structure resilient if it is able to operate correctly (at least) on the set of uncorrupted values. We present a resilient dictionary, implementing search, insert and delete operations. Our dictionary has O(log n + δ) expected amortized time per operation, and O(n) space complexity, where n denotes the current number of keys in the dictionary. We also describe a deterministic resilient dictionary, with the same amortized cost per operation over a sequence of at least δ ǫ operations, where ǫ > 0 is an arbitrary constant. Finally, we show that any resilient comparison-based dictionary must take Ω(log n+δ) expected time per search. Our results are achieved by means of simple, new techniques, which might be of independent interest for the design of other resilient algorithms.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Resilient dictionaries

Finocchi

Grandoni

Italiano

2009

ACM Trans. Algorithms

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“…In particular, it would be interesting to understand whether it is possible to obtain fault-oblivious resilient algorithms, i.e., resilient algorithms that do not assume any knowledge on the maximum number δ of memory faults. In [10,21,25] the problem of designing resilient dictionaries and priority queues has been also addressed: an experimental study of the performances of these resilient data structures would represent a valuable contribution.…”

Section: Discussionmentioning

confidence: 99%

The Price of Resiliency: A Case Study on Sorting with Memory Faults

Petrillo

Finocchi

Italiano

2006

Lecture Notes in Computer Science

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We address the problem of sorting in the presence of faults that may arbitrarily corrupt memory locations, and investigate the impact of memory faults both on the correctness and on the running times of mergesort-based algorithms. To achieve this goal, we develop a software testbed that simulates different fault injection strategies, and perform a thorough experimental study using a combination of several fault parameters. Our experiments give evidence that simple-minded approaches to this problem are largely impractical, while the design of more sophisticated resilient algorithms seems really worth the effort. Another contribution of our computational study is a carefully engineered implementation of a resilient sorting algorithm, which appears robust to different memory fault patterns.

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“…Several problems have been addressed in the faulty-memory RAM, see a recent survey [20] for more information. For instance optimal comparison based sorting algorithms and (static and dynamic) dictionaries [1,[21][22][23], and priority queues [24] have been proposed. In [25] it is shown that resilient sorting algorithms are of practical interest.…”

Section: Introductionmentioning

confidence: 99%

Counting in the Presence of Memory Faults

Brodal

Jørgensen

Moruz

et al. 2009

Algorithms and Computation

Self Cite

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Abstract. The faulty memory RAM presented by Finocchi and Italiano [1] is a variant of the RAM model where the content of any memory cell can get corrupted at any time, and corrupted cells cannot be distinguished from uncorrupted cells. An upper bound, δ, on the number of corruptions and O(1) reliable memory cells are provided. In this paper we investigate the fundamental problem of counting in faulty memory. Keeping many reliable counters in the faulty memory is easily done by replicating the value of each counter Θ(δ) times and paying Θ(δ) time every time a counter is queried or incremented. In this paper we decrease the expensive increment cost to o(δ) and present upper and lower bound tradeoffs decreasing the increment time at the cost of the accuracy of the counters.

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Priority Queues Resilient to Memory Faults

Cited by 32 publications

References 20 publications

Resilient dictionaries

Resilient dictionaries

The Price of Resiliency: A Case Study on Sorting with Memory Faults

Counting in the Presence of Memory Faults

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