Download Algorithm Theory - SWAT 2002 by Penttonen M., Schmidt E.M. PDF

By Penttonen M., Schmidt E.M.

This e-book constitutes the refereed complaints of the eighth Scandinavian Workshop on set of rules conception, SWAT 2002, held in Turku, Finland, in July 2002.The forty three revised complete papers offered including invited contributions have been conscientiously reviewed and chosen from 103 submissions. The papers are equipped in topical sections on scheduling, computational geometry, graph algorithms, robotics, approximation algorithms, information conversation, computational biology, and information garage and manipulation.

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Overmars. A balanced search tree with O(1) worstcase update time. Acta Informatica, 26:269–277, 1988. 14. K. Mehlhorn and S. N¨ aher. Bounded ordered dictionaries in O(log log n) time and O(n) space. Information Processing Letters, 35:183–189, 1990. 15. S. Muthukrishnan and Martin M¨ uller. Time and space efficient method-lookup for object-oriented programs (extended abstract). In Proceedings of the Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, pages 42–51, Atlanta, Georgia, January 28–30 1996.

1 Introduction The Lazy Bureaucrat Scheduling Problem is a modification of traditional scheduling models in which the goal is to minimize, rather than maximize, the amount of work done. The bureaucrat is given a list of jobs that have deadlines. His goal is to do as little work as possible (as defined by a given objective), under the greedy constraint that he must work on a job if one is available (otherwise, the obvious choice would be to do no work at all). Jobs whose deadlines pass before they are completed expire and can no longer be scheduled; this is desirable, since unscheduled jobs reduce the amount of work the bureaucrat needs to do.

This causes a new element to be inserted into the VEB and the binary trees for the two new buckets have to be build. An insertion into the VEB takes O(loglog n) time and uses the same number of memory modifications. Building the binary search trees uses O(log n) time and the same number of memory modifications. When a bucket is split there must have been at least log n insertions into this bucket since it last was involved in a split. That is, splitting and inserting uses O(1) amortized memory modifications per insertion.

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