Download PDF by Alok Aggarwal, C. Pandu Rangan: Algorithms and Computation: 10th International Symposium,

By Alok Aggarwal, C. Pandu Rangan

ISBN-10: 3540466320

ISBN-13: 9783540466321

ISBN-10: 3540669167

ISBN-13: 9783540669166

This ebook constitutes the refereed court cases of the tenth overseas Symposium on Algorithms and Computation, ISAAC'99, held in Chennai, India, in December 1999.
The forty revised complete papers awarded including 4 invited contributions have been conscientiously reviewed and chosen from seventy one submissions. one of the themes coated are facts constructions, parallel and dispensed computing, approximation algorithms, computational intelligence, on-line algorithms, complexity thought, graph algorithms, computational geometry, and algorithms in perform.

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Extra info for Algorithms and Computation: 10th International Symposium, ISAAC’99 Chennai, India, December 16–18, 1999 Proceedings

Example text

This is clear since it waits for 1 time unit after every such downwards step before deleting one thread. The optimum would be 1. Additionally, for every down-up pair of width w, EXPIRY DATE STACK obviously pays w if w < 1, and 2 else, whereas the optimum cost is min{w, 1}. Together this implies the result. A more formal proof might be given by induction. ✷ EXPIRY DATE STACK is easy enough to implement. However it might be more convenient to maintain only constantly many numbers in order to fix the next expiry date, instead of a stack.

Proof. Choose R with tk = ln(1 + (e − 1)k/n). Recall the following properties of any R with tn ≤ 1: We have r = max rk where the rk are the expressions from Lemma 2, and the worst-case ratio of expected cost and t occurs at some t = tk . Now we compare the expected costs of R and KMMO at any fixed t = tk . By our choice of tk , the probability to buy until tk is k/n in both algorithms. It remains to compare the expected rent time. The probability to buy the resource in interval (ti , ti+1 ] is 1/n, but R defers the buy decisions of KMMO until ti+1 .

Biased Search Trees”, J. on Computing 14(3) (1985), 545–568. 6. , Wei, V. , “Splay Trees for Data Compression”, Proc. 6th Symp. on Discrete Algorithms (1995), 522–530. 7. Hu, T. , Tucher, A. , “Optimal Computer Search Trees and Variable-Length Alphabetic Codes”, J. of Applied Mathematics 21(4) (1971), 514–532. 8. Knuth, D. , “Optimum Binary Search Trees”, Acta Informatica 1(1) (1971), 14–25. 9. Overmars, M. , “The Design of Dynamic Data Structures”, Lecture Notes on Computer Science 156, Springer Verlag, 1983.

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Algorithms and Computation: 10th International Symposium, ISAAC’99 Chennai, India, December 16–18, 1999 Proceedings by Alok Aggarwal, C. Pandu Rangan


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