Static Data Structure for Discrete Advance Bandwidth Reservations on the Internet

In this paper we present a discrete data structure for reservations of limited resources. A reservation is defined as a tuple consisting of the time interval of when the resource should be reserved, $I_R$, and the amount of the resource that is reserved, $B_R$, formally $R=\{I_R,B_R\}$. The data structure is similar to a segment tree. The maximum spanning interval of the data structure is fixed and defined in advance. The granularity and thereby the size of the intervals of the leaves is also defined in advance. The data structure is built only once. Neither nodes nor leaves are ever inserted, deleted or moved. Hence, the running time of the operations does not depend on the number of reservations previously made. The running time does not depend on the size of the interval of the reservation either. Let $n$ be the number of leaves in the data structure. In the worst case, the number of touched (i.e. traversed) nodes is in any operation $O(\log n)$, hence the running time of any operation is also $O(\log n)$

Data Structure for a Time-Based Bandwidth Reservations Problem

We discuss a problem of handling resource reservations. The resource can be reserved for some time, it can be freed or it can be queried what is the largest amount of reserved resource during a time interval. We show that the problem has a lower bound of $\Omega(\log n)$ per operation on average and we give a matching upper bound algorithm. Our solution also solves a dynamic version of the related problems of a prefix sum and a partial sum

Reconciling Graphs and Sets of Sets

We explore a generalization of set reconciliation, where the goal is to reconcile sets of sets. Alice and Bob each have a parent set consisting of $s$ child sets, each containing at most $h$ elements from a universe of size $u$. They want to reconcile their sets of sets in a scenario where the total number of differences between all of their child sets (under the minimum difference matching between their child sets) is $d$. We give several algorithms for this problem, and discuss applications to reconciliation problems on graphs, databases, and collections of documents. We specifically focus on graph reconciliation, providing protocols based on set of sets reconciliation for random graphs from $G(n,p)$ and for forests of rooted trees

Učenje glasbe, podprto z IKT tehnologijo

Učenje glasbe podprto z IKT tehnologij

Parse tree based machine translation for less-used languages

The article describes a method that enhances translation performance of language pairs with a less used source language and a widely used target language. We propose a method that enables the use of parse tree based statistical translation algorithms for language pairs with a less used source language and a widely used target language. Automatic part of speech (POS) tagging algorithms have become accurate to the extent of efficient use in many tasks. Most of these methods are quite easily implementable in most world languages. The method is divided in two partsthe first part constructs alignments between POS tags of source sentences and induced parse trees of target language. The second part searches through trained data and selects the best candidates for target sentences, the translations. The method was not fully implemented due to time constraintsthe training part was implemented and incorporated into a functional translation systemthe inclusion of a word alignment model into the translation part was not implemented. The empirical evaluation addressing the quality of trained data was carried out on a full implementation of the presented training algorithms and the results confirm the employability of the method

Parallelization of Ant System for GPU under the PRAM Model

We study the parallelized ant system algorithm solving the traveling salesman problem on n cities. First, following the series of recent results for the graphics processing unit, we show that they translate to the PRAM (parallel random access machine) model. In addition, we develop a novel pheromone matrix update method under the PRAM CREW (concurrent-read exclusive-write) model and translate it to the graphics processing unit without atomic instructions. As a consequence, we give new asymptotic bounds for the parallel ant system, resulting in step complexities O(n łg łg n) on CRCW (concurrent-read concurrent-write) and O(n łg n) on CREW variants of PRAM using n2 processors in both cases. Finally, we present an experimental comparison with the currently known pheromone matrix update methods on the graphics processing unit and obtain encouraging results

An O(1) Solution to the Prefix Sum Problem on a Specialized Memory Architecture

In this paper we study the Prefix Sum problem introduced by Fredman. We show that it is possible to perform both update and retrieval in O(1) time simultaneously under a memory model in which individual bits may be shared by several words. We also show that two variants (generalizations) of the problem can be solved optimally in $\Theta(\lg N)$ time under the comparison based model of computation.Comment: 12 page