Exploiting non-constant safe memory in resilient algorithms and data structures
We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let δ and α denote, respectively, the maximum amount of faults which c...
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| Published in: | Theoretical computer science Vol. 583; pp. 86 - 97 |
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07.06.2015
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| Abstract | We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let δ and α denote, respectively, the maximum amount of faults which can happen during the execution of an algorithm and the actual number of occurred faults, with α≤δ. We propose a resilient algorithm for sorting n entries which requires O(nlogn+α(δ/S+logS)) time and uses Θ(S) safe memory words. Our algorithm outperforms previous resilient sorting algorithms which do not exploit the available safe memory and require O(nlogn+αδ) time. Finally, we exploit our sorting algorithm for deriving a resilient priority queue. Our implementation uses Θ(S) safe memory words and Θ(n) faulty memory words for storing n keys, and requires O(logn+δ/S) amortized time for each insert and deletemin operation. Our resilient priority queue improves the O(logn+δ) amortized time required by the state of the art.
•We study tradeoffs between algorithmic resiliency and hardware resiliency.•We extend the Faulty RAM (FRAM) model by adding a safe memory S which is immune to corruptions.•We propose a resilient sorting algorithm requiring O(nlogn+α(δ/S+logS)) time.•We propose a resilient priority queue data structure requiring O(logn+δ/S) amortized time per operation. |
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| AbstractList | We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let δ and α denote, respectively, the maximum amount of faults which can happen during the execution of an algorithm and the actual number of occurred faults, with α≤δ. We propose a resilient algorithm for sorting n entries which requires O(nlogn+α(δ/S+logS)) time and uses Θ(S) safe memory words. Our algorithm outperforms previous resilient sorting algorithms which do not exploit the available safe memory and require O(nlogn+αδ) time. Finally, we exploit our sorting algorithm for deriving a resilient priority queue. Our implementation uses Θ(S) safe memory words and Θ(n) faulty memory words for storing n keys, and requires O(logn+δ/S) amortized time for each insert and deletemin operation. Our resilient priority queue improves the O(logn+δ) amortized time required by the state of the art.
•We study tradeoffs between algorithmic resiliency and hardware resiliency.•We extend the Faulty RAM (FRAM) model by adding a safe memory S which is immune to corruptions.•We propose a resilient sorting algorithm requiring O(nlogn+α(δ/S+logS)) time.•We propose a resilient priority queue data structure requiring O(logn+δ/S) amortized time per operation. We extend the Faulty RAM model by Finocchi and Italiano (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let delta and alpha denote, respectively, the maximum amount of faults which can happen during the execution of an algorithm and the actual number of occurred faults, with . We propose a resilient algorithm for sorting n entries which requires time and uses safe memory words. Our algorithm outperforms previous resilient sorting algorithms which do not exploit the available safe memory and require time. Finally, we exploit our sorting algorithm for deriving a resilient priority queue. Our implementation uses safe memory words and faulty memory words for storing n keys, and requires amortized time for each insert and deletemin operation. Our resilient priority queue improves the amortized time required by the state of the art. |
| Author | De Stefani, Lorenzo Silvestri, Francesco |
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| Keywords | Memory errors Fault tolerance Tradeoffs Resilient algorithm Resilient data structure Priority queue Sorting |
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| SubjectTerms | Algorithms Fault tolerance Faults Inserts Memory errors Priorities Priority queue Queues Random access memory Resilient algorithm Resilient data structure Sorting Sorting algorithms State of the art Tradeoffs |
| Title | Exploiting non-constant safe memory in resilient algorithms and data structures |
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