SbQA: Une Méthode Auto-Adaptative pour l'Allocation de Requêtes

National audienceWe present a flexible query allocation framework, called {\it Satisfaction-based Query Allocation} (SbQA for short), for distributed information systems where both consumers and providers (the participants) have special interests towards queries. A particularity of SbQA is that it allocates queries while considering both query load and participants' interests. To be fair, it dynamically trades consumers' interests for providers' interests based on their satisfaction. In this demo we illustrate the flexibility and efficiency of SbQA to allocate queries on the {\it Berkeley Open Infrastructure for Network Computing} (BOINC). We also demonstrate that SbQA is self-adaptable to the participants' expectations. Finally, we demonstrate that SbQA can be adapted to different kinds of applications by varying its parameters

BATON: A Balanced Tree Structure for Peer-to-Peer Networks

We propose a balanced tree structure overlay on a peer-to-peer network capable of supporting both exact queries and range queries efficiently. In spite of the tree structure causing distinctions to be made between nodes at different levels in the tree, we show that the load at each node is approximately equal. In spite of the tree structure providing precisely one path between any pair of nodes, we show that sideways routing tables maintained at each node provide sufficient fault tolerance to permit efficient repair. Specifically, in a network with N nodes, we guarantee that both exact queries and range queries can be answered in O(logN) steps and also that update operations (to both data and network) have an amortized cost of O(logN). An experimental assessment validates the practicality of our proposal.Singapore-MIT Alliance (SMA

Un modèle pour caractériser des participants autonomes dans un processus de médiation

Nous considérons les systèmes d'information distribués dans lesquels les participants sont non seulement libres de quitter le système, mais peuvent aussi manifester différents intérêts. La plupart des travaux dans ce contexte sont centrés sur la performance (répartition de charge, temps de réponse. . . ) sans tenir compte des intérêts des participants. Pourtant, le non respect de leurs intérêts particuliers peut conduire les participants à quitter le système. Nous proposons une nouveau modèle qui aide à caractériser la satisfaction des participants sur le long terme ainsi que leur adéquation. We consider distributed information systems where participants are autonomous and have also special interests. Most of the works in this context are centered on the performences but do not take participants' particular interest into account. However, not respeter the particular interests of the participants can lead them to leave the system. We propose a new model that helps to characterize the participants' satisfaction in the long-run as well as their adequation

On Routing in Distributed Hash Tables

There have been many proposals for constructing routing tables for Distributed Hash Tables (DHT). They can be classified into two groups: A) those that assume that the peers are uniformly randomly distributed in the identifier space, and B) those that allow order-preserving hash functions that lead to a skewed peer distribution in the identifier space. Good solutions for group A have been known for many years. However, DHTs in group A are limited to use randomized hashing and therefore, queries over whole identifier ranges thus do not scale. Group B can handle such queries easily. However, it is more difficult to connect the peers such that the resulting topology provides efficient routing, small routing tables, and balanced routing load. We present an elegant new solution to construct an efficient DHT for group B. Our main idea is to decouple the identifier space from the routing topology. In consequence, our DHT allows arbitrarily skewed peer distributions in the identifier space and does not require the overhead of sampling. Furthermore, the table construction is cheap and does not require active replacement of lost routing entries. To evaluate the performance of routing cost and table construction under high churn, we built an efficient simulator. Using the right data structures, we can easily process the state of over one million peers in RAM

Incremental elasticity for array databases

Relational databases benefit significantly from elasticity, whereby they execute on a set of changing hardware resources provisioned to match their storage and processing requirements. Such flexibility is especially attractive for scientific databases because their users often have a no-overwrite storage model, in which they delete data only when their available space is exhausted. This results in a database that is regularly growing and expanding its hardware proportionally. Also, scientific databases frequently store their data as multidimensional arrays optimized for spatial querying. This brings about several novel challenges in clustered, skew-aware data placement on an elastic shared-nothing database. In this work, we design and implement elasticity for an array database. We address this challenge on two fronts: determining when to expand a database cluster and how to partition the data within it. In both steps we propose incremental approaches, affecting a minimum set of data and nodes, while maintaining high performance. We introduce an algorithm for gradually augmenting an array database's hardware using a closed-loop control system. After the cluster adds nodes, we optimize data placement for n-dimensional arrays. Many of our elastic partitioners incrementally reorganize an array, redistributing data only to new nodes. By combining these two tools, the scientific database efficiently and seamlessly manages its monotonically increasing hardware resources.Intel Corporation (Science and Technology Center for Big Data

Libra : une méthode de médiation auto-adaptative en fonction des attentes des participants

National audienceNous considérons le problème de l'allocation de tâches dans le cadre d'environnements ouverts où les participants (fournisseurs et clients) ont des attentes particulières. De nombreux travaux sur l'allocation de tâches se sont concentrés sur des problèmes de maximisation ou de minimisation de fonctions prédéfinies (temps de réponse, répartition de charge...). Cependant, ces objectifs sont définis de manière globale alors que les participants peuvent avoir des objectifs dif- férents, voire divergents. Nous proposons ici une méthode de médiation, Libra, qui s'auto-adapte aux attentes des participants. Libra effectue les allocations en fonction des intérêts individuels des fournisseurs et des clients. Cette prise en compte est régulée par les satisfactions individuelles de sorte à obtenir une certaine équité. Des simulations nous permettent de comparer Libra avec d'autres techniques existantes (répartition de charge, allocation de tâche dans le style de Mariposa). Les résultats montrent que, tout en conservant un haut degré d'efficacité (e.g. temps de réponse), Libra permet aux participants d'atteindre un degré de satisfaction bien supérieur