Randomized permutation routing in multihop ad hoc networks with unknown destinations

A large variety of permutation routing protocols in a single-hop Network are known to day. Since they are single hop, there is always a wireless path connecting two nodes. One way to solve this problem in a multiple hop environment is to partition nodes into clusters, where a node in each cluster called clusterhead is responsible for the routing service. In this paper, we propose a clustering mechanism to perform permutation routing in multi-hop ad hoc Networks having p stations and in which n data items are saved. We first develop a clustering algorithm to partition stations into clusters. Secondly, we run a locally permutation routing to broadcast items to their local destinations in each group. Finally we use a multicast procedure to transmit outgoing items to their final cluster destination.1st IFIP International Conference on Ad-Hoc NetWorkingRed de Universidades con Carreras en Informática (RedUNCI

Randomized permutation routing in multihop ad hoc networks with unknown destinations

A large variety of permutation routing protocols in a single-hop Network are known to day. Since they are single hop, there is always a wireless path connecting two nodes. One way to solve this problem in a multiple hop environment is to partition nodes into clusters, where a node in each cluster called clusterhead is responsible for the routing service. In this paper, we propose a clustering mechanism to perform permutation routing in multi-hop ad hoc Networks having p stations and in which n data items are saved. We first develop a clustering algorithm to partition stations into clusters. Secondly, we run a locally permutation routing to broadcast items to their local destinations in each group. Finally we use a multicast procedure to transmit outgoing items to their final cluster destination.1st IFIP International Conference on Ad-Hoc NetWorkingRed de Universidades con Carreras en Informática (RedUNCI

La programmation dynamique non-serial dans les modèles de calcul parallèle BSP/CGM

Nous assistons cette décennie à une tendance (migration) du hardware parallèle vers les systèmes multiprocesseurs à gros-grain. Cependant, la majorité du logiciel parallèle traditionnel est conçue pour des systèmes grain-fin et pour des machines à mémoire partagée. L'un des principaux défis actuels des chercheurs en conception d'algorithmes parallèles est de réduire cette incompatibilité dite écart logiciel-matériel . Un grand intérêt est ainsi porté à la conception d'algorithmes parallèles efficaces pour les multiprocesseurs gros-grain. C'est dans ce cadre que s'inscrit cette thèse. Nous utilisons le modèle de calcul parallèle BSP/CGM (Bulk synchronous parallel Coarse Grained Multicomputers) pour concevoir des solutions pour des problèmes faisant appel à la technique de programmation dynamique. Nous nous intéressons à un échantillon typique de la programmation dynamique du type polyadique non-serial qui est caractérisée par une très forte dépendance de calculs. Il s'agit d'une importante classe de problèmes largement utilisés dans les applications à haute performance (tel que : le problème d'ordonnancement de produit de chaîne de matrices : OPCM, le problème de l'arbre binaire de recherche optimale : ABRO, le problème de triangulation de polygones convexe : TPC...). Nous présentons tout d'abord une étude détaillée de l'outil de conception, i.e. le modèle BSP/CGM, ainsi qu'une proposition de raffinement du modèle de coût BSP en vue d'améliorer son exactitude de prédiction. Nous présentons ensuite une solution BSP/CGM générique pour la classe de problèmes précitée. Enfin, après une étude des contraintes de l'accélération de cette solution générique dans le modèle BSP/CGM, pour les problèmes OPCM et ABRO, deux algorithmes BSP/CGM accélérés sont proposés.We attend this decade a trend (migration) of the parallel hardware towards coarse-grain multiprocessor systems. However, the majority of the traditional parallel software is designed for fine-grain system and for shared memory machines. One of the main current challenges of the researchers in design of parallel algorithms is to reduce this incompatibility said software-hardware gap . Big interest is so focused on the design of efficient parallel algorithms for coarse-grain multi-processors systems. It's in this context that this thesis contributes. We use the BSP/CGM parallel computing model (Bulk synchronous parallel Coarse Grained Multicomputer) to design solutions for problems using dynamic programming approach. We are interested in a typical sample of the dynamic programming polyadic non-serial which is characterized by a very strong dependence of calculations. It is about an important class of problems widely used in the high-performance applications (MCOP: the matrix chain ordering problem, OBST: the optimal binary search tree problem, CTP: the convex polygons triangulation). We firstly present a detailed study of the design tools, i.e. BSP/CGM model, as well as a proposition of refinement of the BSP cost model to improve its prediction accuracy. We present then a generic BSP/CGM solution for the aforesaid problems class. At the end, after a study of the constraints of the acceleration of this generic solution in BSP/CGM model for the problems MCOP and OBST, two accelerated BSP/CGM algorithms are proposed.AMIENS-BU Sciences (800212103) / SudocSudocFranceF

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