A Grid Based Distributed Cooperative Environment for Health Care Research

International audienceProviding a distributed cooperative environment is a challenging task, which requires a middleware infrastructure that provides, among others, management of distributed shared data, synchronization, consistency, recovery, security and privacy support. In this paper, we present the ECADeG project which proposes a layered architecture for developing distributed cooperative environments running on top of a desktop grid middleware that can encompass multiple organizations. We also present a particular cooperative environment for supporting scientific research focused at the health domain which uses the services supplied by the ECADeG architecture in order to allow researchers to share access to multiple institutions databases, visualize and analyze data by means of data mining techniques, edit research documents cooperatively, exchange information through forums and chats, etc.. Such a rich cooperative environment helps thus the establishment of partnerships between health care professionals and their institutions

Checkpointing of parallel applications in a Grid environment

The Grid environment is generic, heterogeneous, and dynamic with lots of unreliable resources making it very exposed to failures. The environment is unreliable because it is geographically dispersed involving multiple autonomous administrative domains and it is composed of a large number of components. Examples of failures in the Grid environment can be: application crash, Grid node crash, network failures, and Grid system component failures. These types of failures can affect the execution of parallel/distributed application in the Grid environment and so, protections against these faults are crucial. Therefore, it is essential to develop efficient fault tolerant mechanisms to allow users to successfully execute Grid applications. One of the research challenges in Grid computing is to be able to develop a fault tolerant solution that will ensure Grid applications are executed reliably with minimum overhead incurred. While checkpointing is the most common method to achieve fault tolerance, there is still a lot of work to be done to improve the efficiency of the mechanism. This thesis provides an in-depth description of a novel solution for checkpointing parallel applications executed on a Grid. The checkpointing mechanism implemented allows to checkpoint an application at regions where there is no interprocess communication involved and therefore reducing the checkpointing overhead and checkpoint size

Scheduling moldable {BSP} tasks

Our main goal in this paper is to study the scheduling of parallel BSP tasks on clusters of computers. We focus our attention on special characteristics of BSP tasks, which can use less processors than the original required, but with a particular cost model. We discuss the problem of scheduling a batch of BSP tasks on a fixed number of computers. The objective is to minimize the completion time of the last task (makespan). We show that the problem is difficult and present approximation algorithms and heuristics. We finish the paper presenting the results of extensive simulations under different workloads

Analysis of Performance-impacting Factors on Checkpointing Frameworks: The CPPC Case Study

This is a post-peer-review, pre-copyedit version of an article published in The Computer Journal. The final authenticated version is available online at: https://doi.org/10.1093/comjnl/bxr018[Abstract] This paper focuses on the performance evaluation of Compiler for Portable Checkpointing (CPPC), a tool for the checkpointing of parallel message-passing applications. Its performance and the factors that impact it are transparently and rigorously identified and assessed. The tests were performed on a public supercomputing infrastructure, using a large number of very different applications and showing excellent results in terms of performance and effort required for integration into user codes. Statistical analysis techniques have been used to better approximate the performance of the tool. Quantitative and qualitative comparisons with other rollback-recovery approaches to fault tolerance are also included. All these data and comparisons are then discussed in an effort to extract meaningful conclusions about the state-of-the-art and future research trends in the rollback-recovery field.Minsiterio de Ciencia e Innovación; TIN2010-1673

Network and Energy-Aware Resource Selection Model for Opportunistic Grids

Due to increasing hardware capacity, computing grids have been handling and processing more data. This has led to higher amount of energy being consumed by grids; hence the necessity for strategies to reduce their energy consumption. Scheduling is a process carried out to define in which node tasks will be executed in the grid. This process can significantly impact the global system performance, including energy consumption. This paper focuses on a scheduling model for opportunistic grids that considers network traffic, distance between input files and execution node as well as the execution node status. The model was tested in a simulated environment created using GreenCloud. The simulation results of this model compared to a usual approach show a total power consumption savings of 7.10%

Heterogeneous Strong Computation Migration

The continuous increase in performance requirements, for both scientific computation and industry, motivates the need of a powerful computing infrastructure. The Grid appeared as a solution for inexpensive execution of heavy applications in a parallel and distributed manner. It allows combining resources independently of their physical location and architecture to form a global resource pool available to all grid users. However, grid environments are highly unstable and unpredictable. Adaptability is a crucial issue in this context, in order to guarantee an appropriate quality of service to users. Migration is a technique frequently used for achieving adaptation. The objective of this report is to survey the problem of strong migration in heterogeneous environments like the grids', the related implementation issues and the current solutions.Comment: This is the pre-peer reviewed version of the following article: Milan\'es, A., Rodriguez, N. and Schulze, B. (2008), State of the art in heterogeneous strong migration of computations. Concurrency and Computation: Practice and Experience, 20: 1485-1508, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/cpe.1287/abstrac

CHOReOS Middleware Specification (D3.1)

This deliverable specifies the main concepts of the CHOReOS middleware architecture. Starting from the Future Internet (FI) challenges for scalability, heterogeneity, mobility, awareness, and adaptation that have been investigated in prior work done in WP1, we introduce the aforementioned concepts to deal with the requirements derived from the FI challenges. In particular, we propose an extensible and scalable service discovery approach for the organization and discovery of services that relies on multiple service discovery protocols. Moreover, we introduce an extensible and scalable approach, based on the service bus paradigm, for service access that features the integration and adaptation of multiple interaction protocols. Furthermore, we propose solutions that enable the execution of FI service compositions that range from compositions of choreographed services, developed according to the CHOReOS development process, to massive compositions of things. Finally, we detail the Cloud & Grid middleware facilities that support the overall middleware and the choreographies that are built on it, via a unified API that provides access to multiple cloud infrastructures (e.g., Amazon EC2, HP Open Cirrus, private clouds)