An Adaptive Multimedia-Oriented Handoff Scheme for IEEE 802.11 WLANs

Previous studies have shown that the actual handoff schemes employed in the IEEE 802.11 Wireless LANs (WLANs) do not meet the strict delay constraints placed by many multimedia applications like Voice over IP. Both the active and the passive supported scan modes in the standard handoff procedure have important delay that affects the Quality of Service (QoS) required by the real-time communications over 802.11 networks. In addition, the problem is further compounded by the fact that limited coverage areas of Access Points (APs) occupied in 802.11 infrastructure WLANs create frequent handoffs. We propose a new optimized and fast handoff scheme that decrease both handoff latency and occurrence by performing a seamless prevent scan process and an effective next-AP selection. Through simulations and performance evaluation, we show the effectiveness of the new adaptive handoff that reduces the process latency and adds new context-based parameters. The Results illustrate a QoS delay-respect required by applications and an optimized AP-choice that eliminates handoff events that are not beneficial.Comment: 20 pages, 14 figures, 4 table

Aide à la décision pour l'apprentissage

Les travaux réalisés dans cette thèse proposent une aide à la décision pour améliorer la qualité de l apprentissage. L apprentissage scolaire englobe deux dimension; une dimension humaine et une dimension pédagogique. La dimension humaine inclut l apprenant et l enseignant. La dimension pédagogique, représentée par le programme fixé par l établissement éducatif, correspond au savoir. Ce dernier va se transformer en connaissance chez l apprenant. Les deux notions de connaissance et savoir sont donc tout à fait différentes. La distance entre les deux représente la distance entre ce que l enseignant présente (le savoir) et ce que l apprenant acquière (la connaissance). La qualité de l apprentissage concerne les apprenants qui vont à l école pour acquérir le savoir. En fait, apprendre consiste à intérioriser le savoir. Cette intériorisation demande des efforts pour un changement intellectuel persévérant et exige une continuité basée sur les expériences antérieures. L acquisition du savoir et sa transformation en connaissance par l apprenant sont influencées par plusieurs facteurs qui interviennent positivement ou négativement sur la quantité et la qualité de cette connaissance. Il peut résider chez l apprenant une confusion entre les deux notions qui peut l amener à valoriser ou ignorer sa connaissance. Le processus de construction des connaissances par le savoir diffusé exige une constante mise en œuvre de procédures d évaluation. Le processus d évaluation apprécie alors la structure de la connaissance pour prendre des décisions destinées à la faire évoluer. Cependant, lors d une évaluation, la confusion entre connaissance et savoir peut amener l apprenant à valoriser le score, négligeant ainsi le regard qu il pourrait porter sur les processus de transformation des connaissances au profit d une restitution la plus fidèle possible du savoir. Cette confusion peut être mise en évidence pourvu que l évaluation intègre une dimension processuelle. Dès lors, l évaluation peut être mieux associée à des actions d amélioration et de transformation des connaissances. L évaluation peut alors être abordée dans une logique d aide à la décision. Dans ce travail nous montrerons donc qu une situation d apprentissage s apparente à une situation d aide à la décision.The research realized in this thesis proposes a decision support to improve the quality of learning. The learning includes two dimensions; human dimension and pedagogic one. The human dimension includes the learner and the teacher. The pedagogic dimension represented in curriculum set by the educational establishment; it is the know. The learner is going to transform the know into knowledge. Thus the know and the knowledge are two notions completely different. The distance between both is the distance between what the teacher presents (the know) and what the learner acquires (the knowledge). The quality of the learning concerns the learners who go to the school to acquire the know. In fact, learning consists in interiorizing the know. This internalization requires the efforts for persistent intellectual change and demands continuity based on past experiences. The acquisition of knowledge and its transformation into knowledge by the learner is influenced by several factors that affect positively or negatively on the quantity and quality of this knowledge. The confusion between the know and the knowledge guide the learner to value or to ignore his knowledge. The knowledge construction process by the diffused know requires an constant evaluation process. The process of evaluation then appreciates the structure of knowledge to make decisions intended to make it evolve. However, during an evaluation, the confusion between knowledge and knowledge can bring learner to value the score so neglecting the importance which he must give for the transformation knowledge process in favor of the highest possible fidelity of knowledge. This confusion can be detected provided that the evaluation includes a processual dimension. Therefore, the evaluation may be better associated with improvement actions and transformation of knowledge. Then the evaluation can be addressed in a logical decision support. Therefore In this research we demonstrate that the learning situation is a decision aiding situation.VALENCIENNES-Bib. électronique (596069901) / SudocSudocFranceF

A multi-level search strategy for the 0–1 Multidimensional Knapsack Problem

AbstractWe propose an exact method based on a multi-level search strategy for solving the 0–1 Multidimensional Knapsack Problem. Our search strategy is primarily based on the reduced costs of the non-basic variables of the LP-relaxation solution. Considering that the variables are sorted in decreasing order of their absolute reduced cost value, the top level branches of the search tree are enumerated following Resolution Search strategy, the middle level branches are enumerated following Branch & Bound strategy and the lower level branches are enumerated according to a simple Depth First Search enumeration strategy. Experimentally, this cooperative scheme is able to solve optimally large-scale strongly correlated 0–1 Multidimensional Knapsack Problem instances. The optimal values of all the 10 constraint, 500 variable instances and some of the 30 constraint, 250 variable instances of the OR-Library were found. These values were previously unknown

Variable neighbourhood decomposition search for 0-1 mixed integer programs

In this paper we propose a new hybrid heuristic for solving 0-1 mixed integer programs based on the principle of variable neighbourhood decomposition search. It combines variable neighbourhood search with a general-purpose CPLEX MIP solver. We perform systematic hard variable fixing (or diving) following the variable neighbourhood search rules. The variables to be fixed are chosen according to their distance from the corresponding linear relaxation solution values. If there is an improvement, variable neighbourhood descent branching is performed as the local search in the whole solution space. Numerical experiments have proven that exploiting boundary effects in this way considerably improves solution quality. With our approach, we have managed to improve the best known published results for 8 out of 29 instances from a well-known class of very di±cult MIP problems. Moreover, computational results show that our method outperforms the CPLEX MIP solver, as well as three other recent most successful MIP solution methods

An iterative variable-based fixation heuristic for the 0-1 multidimensional knapsack problem

An iterative scheme which is based on a dynamic fixation of the variables is developed to solve the 0-1 multidimensional knapsack problem. Such a scheme has the advantage of generating memory information, which is used on the one hand to choose the variables to fix either permanently or temporarily and on the other hand to construct feasible solutions of the problem. Adaptations of this mechanism are proposed to explore different parts of the search space and to enhance the behaviour of the algorithm. Encouraging results are presented when tested on the correlated instances of the 0-1 multidimensional knapsack problem.Heuristics Exact methods Fixation techniques Knapsack

Extension of Reverse Elimination Method Through a Dynamic Management of the Tabu List

The Reverse Elimination Method (REM) is a dynamic strategy for managing the tabu list. It is based on logical interdependencies between the solutions encountered during recent iterations of the search. REM provides both a necessary and sufficient condition to prevent cycling. The purpose of this paper is first to incorporate in REM a chronological order rule when cycling is unavoidable, thereby assuring the finite convergence of Tabu Search. Secondly, we correct a generalization of REM, the so-called REM-t method proposed by Glover (1990) where t is an integer parameter which controls the number of tabu attributes. A suitable adjustment of this parameter t can be designed in order to create a balance between diversification and intensification. In this paper, new dynamic rules for controlling the adjustment of the parameter t, are proposed. Finally, to illustrate the differences between the variants proposed for managing the tabu list, we test some of them on the 0–1 multidimensional knapsack problem

Heuristiques hybrides pour la résolution de problèmes en variables 0-1 mixtes

Les problèmes d optimisation en variables 0-1 mixtes permettent de modéliser de nombreux problèmes réels difficiles à résoudre. Cette thèse s intéresse à la mise en œuvre de méthodes de résolution hybrides pour obtenir des solutions de bonne qualité en des temps raisonnables pour ces problèmes. L ensemble des algorithmes présentés dans cette thèse est testé sur le problème du sac-à-dos multidimensionnel qui consiste à maximiser une fonction linéaire en respectant un ensemble de contraintes linéaires. Nous présentons dans le premier chapitre différents problèmes de la famille du sac-à-dos. Nous abordons dans le second chapitre un ensemble de méthodes efficaces existantes pour résoudre le problème du sac-à-dos multidimensionnel. Nous proposons dans le chapitre 3 une première méthode hybride qui combine la programmation dynamique et la recherche tabou au sein d un processus dit d intensification globale. Des concepts de réduction sont intégrés dans la programmation dynamique pour essayer de réduire la taille du problème. La seconde approche décrite dans le chapitre 4 combine la recherche dispersée avec des éléments de la recherche tabou et des chemins reliants pour affiner la recherche. Une étude expérimentale est menée pour mesurer l impact de différents composants de l algorithme. Le chapitre 5 présente une approche utilisant conjointement la relaxation en continu et la relaxation en nombres entiers mixtes pour résoudre efficacement les problèmes en variables 0-1. Un ensemble de résultats numériques est présenté pour chacune des méthodes. La dernière permet d améliorer quelques meilleures valeurs connues sur des instances existantes de sac-à-dos multidimensionnel.The 0-1 mixed integer programs represent many difficult real problems. The subject of this thesis is the proposition of hybrid methods to obtain good solutions in reasonable time for these problems. All the algorithms presented in this thesis are tested on the ultidimensional knapsack problem. It consists on the maximisation of a linear function with the respect of a set of linear constraints. In the first chapter of this thesis, we give a few concepts used to solve optimisation problems. We also present some problems of the knapsack problem family. We then present in the second chapter a state of the art to solve the multidimensional knapsack problem. We propose in the third chapter a first hybrid method. It combines a dynamic programming approach with a tabu search algorithm in a global intensification process. Some reduction rules are also integrated in the dynamic programming phase to try to reduce the size of the problem. The second approach is described in the chapter 4. It combines a scatter search algorithm with tabu search and path relinking components to enhance the process. We present an experimental study to assess the impact of some elements of the algorithm. We finally present in the chapter 5 some heuristics using jointly the linear programming relaxation and the mixed integer linear programming relaxation to solve the 0-1 integer programs. A set of computational results is presented for each approach. The last one improves some best-known values on a set of available instances of multidimensional knapsack problemVALENCIENNES-BU Sciences Lettres (596062101) / SudocSudocFranceF