Exploitation of Best Effort Distributed Computing Infrastructures (BE-DCIs) allow operators to maximize the utilization of the infrastructures, and users to access the unused resources at relatively low cost. Because providers do not guarantee that the computing resources remain available to the user during the entire execution of their applications, they offer a diminished Quality of Service (QoS) compared to traditional infrastructures. Profiling the execution of Bag-of-Tasks (BoT) applications on several kinds of BE-DCIs demonstrates that their task completion rate drops near the end of the execution.

Desktop Grids and Service Grids are widely used by scientific communities to execute high throughput application. The European EDGeS project aims at developing the technologies to bridge these two kinds of Grid technologies together. In this paper, we present the development and the application of these new technology to extend the EGEE Grid with XtremWeb-HEP based Desktop Grids. We present the setup of the distributed infrastructure which enables EGEE users' jobs to run on one of the three various XtremWeb-HEP DGs. We describe the new volunteer computing project EGEE@Home based on XtremWeb-HEP middleware. To evaluate the capacity of our technology, we present a performance measurement of the main components and conclude that the overhead is kept reasonable despite the fact that the infrastructure is highly distributed.

Desktop Grids harvest the computing power of idle desktop computers whether these are volunteer or deployed at an institution. Allowing foreign applications to run on these resources requires the sender of the application to be trusted, but trust in goodwill is never enough. An efficient solution is to provide a secure isolated execution environment ("sandbox"), which does not constrain any additional burden neither on administrators nor on users. Currently Desktop Grids do not provide such facility. In this paper we investigate methods and mechanisms that enable the use of virtual machines as part of a security infrastructure for Desktop Grid clients to provide a sandbox for running (untrusted) applications. We define and analyze the requirements for any platform independent and transparent sandbox for Desktop Grids. We detail a prototype, which we built based on our findings and we give a performance evaluation.

EDGeS is an European funded Framework Program 7 project that aims to connect desktop and service grids together. While in a desktop grid, personal computers pull jobs when they are idle, in service grids there is a scheduler that pushes jobs to available resources. The work in EDGeS goes well beyond conceptual solutions to bridge these grids together: it reaches as far as actual implementation, standardization, deployment, application porting and training. One of the work packages of this project concerns monitoring the overall EDGeS infrastructure. Currently, this infrastructure includes two types of desktop grids, BOINC and XtremWeb, the EGEE service grid, and a couple of bridges to connect them. In this paper, we describe the monitoring effort in EDGeS: our technical approaches, the goals we achieved, and the plans for future work.

RPC is one of the programming models envisioned for the Grid. In Internet connected Large Scale Grids such as Desktop Grids, nodes and networks failures are not rare events. This paper provides several contributions, examining the feasibility and limits of fault-tolerant RPC on these platforms. First, we characterize these Grids from their fundamental features and demonstrate that their applications scope should be safely restricted to stateless services. Second, we present a new fault-tolerant RPC protocol associating an original combination of three-tier architecture, passive replication and message logging. We describe RPC-V, an implementation of the proposed protocol within the XtremWeb Desktop Grid middleware. Third, we evaluate the performance of RPC-V and the impact of faults on the execution time, using a real life application on a Desktop Grid testbed assembling nodes in France and USA. We demonstrate that RPC-V allows the applications to continue their execution while key system components fail.

Grid computing presents two major challenges for deploying large scale applications across wide area networks gathering volunteers PC and clusters/parallel computers as computational resources: security and fault tolerance. This paper presents a lightweight Grid solution for the deployment of multi-parameters applications on a set of clusters protected by firewalls. The system uses a hierarchical design based on Condor for managing each cluster locally and XtremWeb for enabling resource sharing among the clusters. We discuss the security and fault tolerance mechanisms used for this design and demonstrate the usefulness of the approach measuring the performances of a multi-parameters bio-chemistry application deployed on two sites: University of Wisconsin/Madison and Paris South University. This experiment shows that we can efficiently and safely harness the computational power of about 200 PC distributed on two geographic sites.

Global Computing platforms, large scale clusters and future TeraGRID systems gather thousands of nodes for computing parallel scientific applications. At this scale, node failures or disconnections are frequent events. This Volatility reduces the MTBF of the whole system in the range of hours or minutes. We present MPICH-V, an automatic Volatility tolerant MPI environment based on uncoordinated checkpoint/roll-back and distributed message logging. MPICH-V architecture relies on Channel Memories, Checkpoint servers and theoretically proven protocols to execute existing or new, SPMD and Master-Worker MPI applications on volatile nodes. To evaluate its capabilities, we run MPICH-V within a framework for which the number of nodes, Channels Memories and Checkpoint Servers can be completely configured as well as the node Volatility. We present a detailed performance evaluation of every component of MPICH-V and its global performance for non-trivial parallel applications. Experimental results demonstrate good scalability and high tolerance to node volatility.