Julien Gossa

Proactive Replica Placement Using Mobility Prediction

In mobile distributed computing scenarios, data replication management can be enhanced by considering client mobility. This work introduces a mobility model for mobile clients which enables proactive replica placement based on mobility predictions to increase the responsiveness of data access for mobile end users and to reduce the network load in the system. The concept is applied to a flexible replica placement algorithm and is evaluated using GPS traces generated by taxis in the city of Vienna, Austria. We show results demonstrating that replica placement can be improved by adding mobility prediction and discuss the influences of prediction accuracy on the accuracy of the placement strategy.

GGM: Efficient Navigation and Mining in Distributed Genomedical Data

The integration of genomics and patient related data is considered as one of the most promising investigation topic in health care research. Started in 2004, the Grid for Geno Medicine (GGM) project aims at providing a comprehensive grid software infrastructure designed to allow biologists to mine and analyze relationships between medical, genetic, and genomic data stored in distributed datawarehouses. The proposed layered service oriented architecture offers a number of independent but compliant services that can be deployed in a grid environment. This paper presents these services insisting on their integration into a common software platform, the use case that is carried out. It also presents the current state of the developments and of the performance evaluations.

Evaluation of network distances properties by NDS, the Network Distance Service

This article presents a novel method for evaluating the properties of distances between hosts in a computational grid. Our method allows obtaining several indicators about a given network. We demonstrate why the current monitoring tools are not sufficient in grid environments that lack high level tools taking into account particular constraints for some given applications. We show how this method has been embedded in a grid service, namely the network distance service (NDS). Basically, this service returns the evaluation and characterization of a distance between a given set of sources and destinations. We illustrate the benefit of our approach in terms of accuracy of the returned values. We explain some implementation issues and discuss how the proposed NDS service can be useful to any grid service who needs some accurate evaluation for a decision making process involving such distances.

A monitoring service for large-scale dynamic query optimisation in a grid environment

The execution plans generated by the traditional optimisers for large-scale distributed queries in a grid can be suboptimal for the following reasons: the centralisation of decisions made by the optimiser; the inaccuracy of estimations; the unavailability of up-to-date description of resources. In this paper, we propose an approach to improve the estimation of the execution cost of a query (or part of a query) in a grid environment by using Mobile Agents (MAs) and runtime monitoring information. First, Mas allow dynamic optimisation in a decentralised and autonomous way. Second, the retrieval of the monitoring information causes some issues addressed by a dedicated service called the Network Distance Service (NDS). The performance evaluation shows that our approach allows a better estimation of the execution cost of a query in a grid and a large benefit to monitor the CPU for a mobile join when the subestimation errors increase while the benefit to monitor the bandwidth is poor.

When the grid becomes pervasive to save the day, even Mitch Buchannon needs decision-making support

The merging of grid and pervasive computing raises new challenges. Its main impact is a critical increase of the dynamicity, heterogeneity and unpredictability of users, usages and even network topology. Moreover emergency scenarii are one of the most important target applications of pervasive grids: With strong time constraints the performances become a critical point and the decisions about the distribution become a key of the efficiency. However existing grid middlewares have been designed for quite stable, homogeneous, and predictable architectures. Our proposal is a distribution decision-making support designed to be easy, usable, and profitable. We present a use case of pervasive grid and demonstrate why existing solutions are not adapted. We show how our method has been embedded in a grid web service, namely the Network Distance Service (NDS) and illustrate its benefit on the main problems of distribution: replication, placement and selection. We show experimentation results and discuss how NDS handles the new constraints involved by the merging of grid and pervasive computing.

Adaptable distance-based decision-making support in dynamic cross-grid environment

The grid environment presents numerous opportunities for business applications as well as for scientific ones. Nevertheless the current trends seem to lead to several independent specialized grids in opposition to the early visions of one generic world wide grid. In such a cross-grid context, the environment might be harder to manipulate whereas more decisions must be handled from user-side. Our proposal is a distance-based decision-making support designed to be usable, adaptable and accurate. Our main contribution is to ensure the profitability of classical monitoring solutions by improving their usability. Our approach is illustrated and validated with experiments in a real grid environment.

End-to-End Distance Computation in Grid Environment by NDS, the Network Distance Service

This article presents a novel method for computing distances between hosts in a computational grid. Our method allows to represent the cost to achieve any operation involving some services in a grid environment. We demonstrate why the current monitoring tools are not sufficient in grid environments that lack high level tools to combine several sources of monitoring while taking into account particular constraints for some given applications. We show how this method has been embedded in a grid service, namely the network distance service (NDS). We illustrate the benefit of our approach in terms of accuracy, using an algorithm from graph theory on a grid planning scenario. We explain some implementation issues and discuss how the proposed NDS service can be useful to any grid service who needs some accurate evaluation for a decision making process involving such distances

Multi-ressources K-Médians: un algorithme de placement de services web sur les réseaux sans fils municipaux

Nowadays, numerous municipalities are laying free wireless Internet access infrastructures on. These infrastructures are a natural target for the deployment of Web services, such as mapping or multimedia content providing. Regarding the number of clients, ensuring their performances represents one particularly important challenge. Unfortunately, this challenge is hard because of Web services peculiarities: difficult to migrate and replicate, heterogeneous, and highly interdependent. Our proposal is an algorithm designed to build deployment plans for sets of Web services, according to their interdependency while ensuring performances and load balancing. We have shown the efficiency of this algorithm, called MRKM for Multi-Resources K-Median, on the Grid 5000 experimental platform.

Replica placement in a pervasive environment

This short paper proposes a replica placement and selection method adapted to pervasive environment. The described solution, based on Small Worlds and the k-server algorithm, is dynamic and flexible according to the mobility and unpredictability of users and networks.