Fault Tolerant Resource Allocation for Query Processing in Grid Environments

International audienceIn this paper, we propose a new algorithm for fault-tolerant resource allocation for query processing in grid environments. For this, we propose an initial resource allocation algorithm followed by a fault-tolerance protocol. The proposed fault-tolerance protocol is based on the passive replication of stateful operators in queries. We provide theoretical analyses of the proposed algorithms and consolidate our analyses with the simulations

Resource allocation for query processing in grid systems: A survey

Grid systems are very useful platforms for distributed databases, especially in some situations in which the scale of data sources and user requests is very high. However, the main characteristics of grid systems such as dynamicity, large size and heterogeneity, bring new problems to the query processing domain such as resource discovery and resource allocation. In this paper, we provide a survey related to resource allocation methods for query processing In data grid systems. We provide a classification for existing studies considering their approaches to the resource allocation problem. We provide a synthesis of the studies and propose evaluations and comparisons for the different classes of studies. ©2012 CRL Publishing Ltd

Self-optimizing block transfer in web service grids

Nowadays, Web Services (WSs) play an increasingly impor-tant role in Web data management solutions, since they offer a practical solution for accessing and manipulating data sources spanning administrative domains. Neverthe-less, they are notoriously slow and transferring large data volumes across WSs becomes the main bottleneck in such WS-based applications. This paper deals with the problem of minimizing at runtime, in a self-managing way, the data transfer cost of a WS encapsulating a data source. To reduce the transfer cost, the data volume is typically divided into blocks. In this case, response time exhibits a quadratic-like, non-linear behavior with regards to the block size; as such, minimizing the transfer cost entails finding the optimum block size. This situation is encountered in several systems

A bi-objective cost model for optimizing database queries in a multi-cloud environment

AbstractCost models are broadly used in query processing to drive the query optimization process, accurately predict the query execution time, schedule database query tasks, apply admission control and derive resource requirements to name a few applications. The main role of cost models is to estimate the time needed to run the query on a specific machine. In a multi-cloud environment, cost models should be easily calibrated for a wide range of different physical machines, and time estimates need to be complemented with monetary cost information, since both the economic cost and the performance are of primary importance. This work aims to serve as the first proposal for a bi-objective query cost model suitable for queries executed over resources provided by potentially multiple cloud providers. We leverage existing calibrating modeling techniques for time estimates and we couple such estimates with monetary cost information covering the main charging options for using cloud resources. Moreover, we explain how the cost model can become part of an optimizer. Our approach is applicable to more generic data flow graphs, the execution plans of which do not necessarily comprise relational operators. Finally, we give a concrete example about the usage of our proposal and we validate its accuracy through real case studies

Découverte et allocation des ressources pour le traitement de requêtes dans les systèmes grilles

De nos jours, les systèmes Grille, grâce à leur importante capacité de calcul et de stockage ainsi que leur disponibilité, constituent l'un des plus intéressants environnements informatiques. Dans beaucoup de différents domaines, on constate l'utilisation fréquente des facilités que les environnements Grille procurent. Le traitement des requêtes distribuées est l'un de ces domaines où il existe de grandes activités de recherche en cours, pour transférer l'environnement sous-jacent des systèmes distribués et parallèles à l'environnement Grille. Dans le cadre de cette thèse, nous nous concentrons sur la découverte des ressources et des algorithmes d'allocation de ressources pour le traitement des requêtes dans les environnements Grille. Pour ce faire, nous proposons un algorithme de découverte des ressources pour le traitement des requêtes dans les systèmes Grille en introduisant le contrôle de topologie auto-stabilisant et l'algorithme de découverte des ressources dirigé par l'élection convergente. Ensuite, nous présentons un algorithme d'allocation des ressources, qui réalise l'allocation des ressources pour les requêtes d'opérateur de jointure simple par la génération d'un espace de recherche réduit pour les nœuds candidats et en tenant compte des proximités des candidats aux sources de données. Nous présentons également un autre algorithme d'allocation des ressources pour les requêtes d'opérateurs de jointure multiple. Enfin, on propose un algorithme d'allocation de ressources, qui apporte une tolérance aux pannes lors de l'exécution de la requête par l'utilisation de la réplication passive d'opérateurs à état. La contribution générale de cette thèse est double. Premièrement, nous proposons un nouvel algorithme de découverte de ressource en tenant compte des caractéristiques des environnements Grille. Nous nous adressons également aux problèmes d'extensibilité et de dynamicité en construisant une topologie efficace sur l'environnement Grille et en utilisant le concept d'auto-stabilisation, et par la suite nous adressons le problème de l'hétérogénéité en proposant l'algorithme de découverte de ressources dirigé par l'élection convergente. La deuxième contribution de cette thèse est la proposition d'un nouvel algorithme d'allocation des ressources en tenant compte des caractéristiques de l'environnement Grille. Nous abordons les problèmes causés par la grande échelle caractéristique en réduisant l'espace de recherche pour les ressources candidats. De ce fait nous réduisons les coûts de communication au cours de l'exécution de la requête en allouant des nœuds au plus près des sources de données. Et enfin nous traitons la dynamicité des nœuds, du point de vue de leur existence dans le système, en proposant un algorithme d'affectation des ressources avec une tolérance aux pannes.Grid systems are today's one of the most interesting computing environments because of their large computing and storage capabilities and their availability. Many different domains profit the facilities of grid environments. Distributed query processing is one of these domains in which there exists large amounts of ongoing research to port the underlying environment from distributed and parallel systems to the grid environment. In this thesis, we focus on resource discovery and resource allocation algorithms for query processing in grid environments. For this, we propose resource discovery algorithm for query processing in grid systems by introducing self-stabilizing topology control and converge-cast based resource discovery algorithms. Then, we propose a resource allocation algorithm, which realizes allocation of resources for single join operator queries by generating a reduced search space for the candidate nodes and by considering proximities of candidates to the data sources. We also propose another resource allocation algorithm for queries with multiple join operators. Lastly, we propose a fault-tolerant resource allocation algorithm, which provides fault-tolerance during the execution of the query by the use of passive replication of stateful operators. The general contribution of this thesis is twofold. First, we propose a new resource discovery algorithm by considering the characteristics of the grid environments. We address scalability and dynamicity problems by constructing an efficient topology over the grid environment using the self-stabilization concept; and we deal with the heterogeneity problem by proposing the converge-cast based resource discovery algorithm. The second main contribution of this thesis is the proposition of a new resource allocation algorithm considering the characteristics of the grid environment. We tackle the scalability problem by reducing the search space for candidate resources. We decrease the communication costs during the query execution by allocating nodes closer to the data sources. And finally we deal with the dynamicity of nodes, in terms of their existence in the system, by proposing the fault-tolerant resource allocation algorithm