We present MobiDesk, a mobile virtual desktop computing hosting infrastructure that leverages continued improvements in network speed, cost, and ubiquity to address the complexity, cost, and mobility limitations of today’s personal computing infrastructure. MobiDesk transparently virtualizes a user’s computing session by abstracting underlying system resources in three key areas: display, operating system and network. MobiDesk provides a thin virtualization layer that decouples a user’s computing session from any particular end user device and moves all application logic from end user devices to hosting providers. MobiDesk virtualization decouples a user’s computing session from the underlying operating system and server instance, enabling high availability service by transparently migrating sessions from one server to another during server maintenance or upgrades. We have implemented a MobiDesk prototype in Linux that works with existing unmodified applications and operating system kernels. Our experimental results demonstrate that MobiDesk has very low virtualization overhead, can provide a full-featured desktop experience including full-motion video support, and is able to migrate users’ sessions efficiently and reliably for high availability, while maintaining existing network connections.

Utilizing a collection of workstations and supercomputers in a metacomputing environment does not only offer an enormous amount of computing power, but also raises new problems. The true potential of WAN-based distributed computing can only be exploited if the application-to-architecture mapping reflects the different processor speeds, network performances and the application's communication characteristics. In this paper, we present the Metacomputer Adaptive Runtime System MARS,a framework for minimizing the execution time of distributed applications on a WAN metacomputer. Work-load balancing and task migration is based on dynamic information on the processor load and network performance. Moreover, MARS uses accumulated statistical data on previous execution runs of the same application to derive an improved task-to-process mapping. Migration decisions are based on (1) the current system load, (2) the network load and (3) previously obtained application-specific characteri...

This paper describes Stardust, an environment for parallel programming on networks of heterogeneous machines. Stardust runs on distributed memory multicomputers and networks of workstations. Applications using Stardust can communicate both through message-passing and distributed shared memory. Stardust includes a mechanism for application reconfiguration. This mechanism is used for balancing the load of the machines hosting the application, as well as for tolerating machine restarts (anticipated or not). At reconfiguration time, application processes can migrate between heterogeneous machines, and the number of application processes can vary (increase or decrease) depending on the available resources. Stardust is currently implemented on an heterogeneous system including an Intel Paragon running Mach/OSF1 and a set of Pentiums running Chorus/classiX. The paper details the design and implementation of Stardust, as well as its performance. Contact author Isabelle Puaut IRISA, Campus Uni...

Networks of workstations (NOWs) offer a cost effective platform for high-performance, long-running parallel computations. However, these computations must be able to tolerate the changing and often faulty nature of NOW environments. We present high-performance implementations of several fault-tolerant algorithms for distributed scientific computing. The fault-tolerance is based on diskless checkpointing, a paradigm that uses processor redundancy rather than stable storage as the fault-tolerant medium. These algorithms are able to run on clusters of workstations that change over time due to failure, load or availability. As long as there are at least n processors in the cluster, and failures occur singly, the computation will complete in an efficient manner. We discuss the details of how the algorithms are tuned for fault-tolerance and present the performance results on a PVM network of Sun workstations connected by a fast, switched ethernet.

P-GRADE provides a high-level graphical environment to develop parallel applications transparently both for parallel systems and the Grid. P-GRADE supports the interactive execution of parallel programs as well as the creation of a Condor,Condor-G or Globus job to execute parallel programs in the Grid. In P-GRADE, the user can generate either PVM or MPI code according to the underlying Grid where the parallel application should be executed. PVM applications generated by P-GRADE can migrate between different Grid sites and as a result P-GRADE guarantees reliable, fault-tolerant parallel program execution in the Grid. The GRM/PROVE performance monitoring and visualisation toolset has been extended towards the Grid and connected to a general Grid monitor (Mercury) developed in the EU GridLab project. Using the Mercury/GRM/PROVE Grid application monitoring infrastructure any parallel application launched by P-GRADE can be remotely monitored and analysed at run time even if the application migrates among Grid sites. P-GRADE supports workflow definition and co-ordinated multi-job execution for the Grid. Such workflow management can provide parallel execution at both inter-job and intra-job level. Automatic checkpoint mechanism for parallel programs supports the migration of parallel jobs inside the workflow providing a fault-tolerant workflow execution mechanism. The paper describes all of these features of P-GRADE and their implementation concepts.

Continuing advances in hardware technology have enabled the proliferation of faster, cheaper, and more capable personal computers. Users of all backgrounds rely on their computers to handle ever-expanding information, communication, and computation needs. As users spend more time interacting with their computers, it is becoming increasingly important to archive and later search the knowledge, ideas and information that they have viewed through their computers. However, existing state-of-the-art web and desktop search tools fail to provide a suitable solution, as they focus on static, accessible documents in isolation. Thus, finding the information one has viewed among the ever-increasing and chaotic sea of data available from a computer remains a challenge. This dissertation introduces DejaView, a personal virtual computer recorder that enhances personal computers with the ability to process display-centric content to help users with all the information they see through their computers. DejaView

Many practical scientific computer applications would benefit from a simple checkpointing mechanism that provides automatic restart or recovery in response to faults and failures, and enables dynamic load balancing and improved resource utilization using task migration. However, developing applications with such capabilities, especially in distributed, heterogeneous operating environments, is very challenging. CUMULVS is a middleware infrastructure for interacting with parallel scientific simulation programs and supports online visualization and computational steering. Using semantic information provided by user-level specifications of selected program variables, CUMULVS interprets distributed data decompositions across heterogeneous collections of computing resources. It extracts and assembles subsets of local decomposed application data to form global views of the data. The base CUMULVS system has been extended to provide a user-level mechanism that assists in the collection of check...

With the increased use of networks of NT workstations for long-running engineering applications, process checkpointing and process migration can avoid wasted computer cycles and improve system utilization. The problem we solve is how to capture and reconstruct process state transparently and efficiently without affecting the correctness of the application. A checkpoint facility enables the intermediate state of a process to be saved to a file. Users can later resume execution of the process from the checkpoint file. This prevents the loss of data generated by long-running processes due to program or system failures, and it also facilitates debugging when the bug appears after the program has executed for a long time. This paper describes the implementation of a checkpoint library that permits users to save temporary state of long-running multi-threaded programs on a Windows/NT system and to resume execution from the checkpointed state at a later time. Our Windows implementation is th...

. Gardens is an integrated programming language and system supporting parallel computation across networks of workstations. It addresses a combination of goals: it (i) maximises performance and (ii) is still safe, it supports (iii) the programming of abstractions (parallel libraries) and (iv) adaptive parallel computation, ie, computation that adapts at run-time to a changing set of available workstations. In Gardens, tasks represent units of work and task migration supports adaptation: releasing workstations on demand. To support adaptation, problems are over-decomposed into more tasks than processors. Tasking is non-preemptive: simplifying semantics and admitting a very efficient implementation. Within its local heap, each task manages a collection of global objects. These support: communication via global methods which other tasks may invoke, abstraction and typed safe asynchronous communication (including freedom from self-inflicted and distributed network deadlocks). The implement...

Abstract. This paper evaluates the impact of task migration on gangscheduling of parallel jobs for distributed systems. With migration, it is possible to move tasks of a job from their originally assigned set of nodes to another set of nodes, during execution of the job. This additional exibility creates more opportunities for lling holes in the scheduling matrix. We conduct a simulation-based study of the e ect of migration on average job slowdown and wait times for a large distributed system under a variety of loads. We nd that migration can signi cantly improve these performance metrics over an important range of operating points. We also analyze the e ect of the cost of migrating tasks on overall system performance. 1