Chapitre VIII Conclusion et perspectives
2. Perspectives
2.2. Extension des méthodes de prise en compte des contraintes liées à la mobilité
Premièrement, rappelons que nous avons proposé deux méthodes pour le traitement des requêtes RDL continues. Actuellement, nous utilisons le prototype développé pour évaluer les performances de chacune des méthodes proposées afin de les comparer. Ces expériences permettront d’identifier les facteurs ayant un impact sur les performances de chacune des méthodes (e.g. nombre d’accès disque, utilisation de la mémoire, utilisation du processeur). Le but est d’ajouter à notre architecture une composante qui choisit, lors du traitement d’une requête continue, la méthode à employer en fonction de certains paramètres identifiés lors des évaluations des performances (e.g. vitesse du client, distance précisée par l’utilisateur, état du système). Il en est de même pour le traitement des requêtes RDL à résultats partiels. Rappelons que pour le traitement de ces requêtes, nous avons proposé également deux méthodes.
D’un autre côté, les méthodes de traitement des requêtes RDL proposées ne tiennent pas compte des trajectoires complètes des objets mobiles. Rappelons que nous supposons que les localisations de ces objets sont mises à jour périodiquement par le système de localisation. Comme nous l’avons précisé dans l’état de l’art, d’autres modèles ont été proposés pour représenter le mouvement de l’objet et notamment sa trajectoire complète [SWC+ 97, GBE+ 00, RSS 03, TDS 05]. Il est possible de tenir compte de ces modèles dans notre architecture. Toutefois, certains algorithmes proposés nécessitent d’être adaptés au modèle choisi pour la représentation de la localisation des objets mobiles. Notons, par ailleurs, que pour interroger des données relatives aux localisations futures des clients et des objets mobiles, il est nécessaire d’anticiper leurs mouvements. Dans notre travail, pour prédire les localisations futures des clients mobiles, nous avons supposé que ces derniers possèdent une vitesse et une direction constantes. Certains travaux liés au domaine de la mobilité se sont focalisés sur la prédiction de la localisation future des objets mobiles [SJL 00, JHT+ 07]. Ils proposent des solutions permettant de tenir compte des changements de direction et de vitesse des clients pendant le traitement des requêtes. Etudier les techniques proposées en vue de les intégrer dans notre architecture permet d’améliorer le pourcentage de résultats corrects des résultats des requêtes RDL qui portent sur la localisation future des clients et des objets mobiles.
En conclusion, nous avons conçu dans cette thèse une architecture générique qui a nécessité la proposition d’un langage d’expression et des méthodes pour le traitement des requêtes dépendant de la localisation avec des contraintes de temps réel. Ces propositions ouvrent la voix à plusieurs perspectives. Nous avons cité celles qui nous semblent les plus pertinentes en rapport avec le traitement des requêtes RDL avec des contraintes de temps réel. Il convient de signaler que la liste des perspectives présentée dans cette section n’est pas exhaustive. Nous espérons, néanmoins, que les éléments présentés participent à alimenter le débat et à ouvrir la porte à de nouvelles orientations de recherche.
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[XHL 05] M. Xiong, S. Han, K. Y. Lam. A Deferrable Scheduling Algorithm for Real- Time Transactions Maintaining Data Freshness. In Proc. of the 26th IEEE International Real-Time Systems Symposium, RTSS’05, 2005, pp. 27-37. [XRS+ 02] M. Xiong, K. Ramamritham, J. A. Stankovic, D. F. Towsley, R. M.
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[XMW+ 04] Xiaopeng Xiong, Mohamed F. Mokbel, Walid G. Aref, Susanne E. Hambrusch, Sunil Prabhakar: Scalable Spatio-temporal Continuous Query Processing for Location-aware Services. SSDBM, 2004, pp. 317-327.
[ZLL 04] B. Zheng, W. C. Lee, D. L. Lee. On Semantic Caching and Query Scheduling for Mobile Nearest-Neighbor Search. Wireless Networks, 10(6), 653-664, (2004).
[ZMS 03] Q. Zhu, S. Motheramgari, Y. Sun. Cost Estimation for Queries Experiencing Multiple Contention States in Dynamic Multidatabase Environments.