Application Invocation Research Articles

Shuttle: Facilitating Inter-Application Interactions for OS-Level Virtualization

OS-level virtualization generates a minimal start-up and run-time overhead on the host OS and thus suits applications that require both good isolation and high efficiency. However, multiple-member applications required for forming a system may need to occasionally communicate across this isolation barrier to cooperate with each other while they are separated in different VMs to isolate intrusion or fault. Such application scenarios are often critical to enterprise-class servers, HPC clusters and intrusion/fault-tolerant systems, etc. We make the first effort to support the inter-application interactions in an OS-level virtualization system without causing a significant compromise on VM isolation. We identify all interactive operations that impact inter-application interactions, including inter-process communications, application invocations, resource name transfers, and application dependencies. We propose Shuttle, a novel approach for facilitating inter-application interactions within and across OS-level virtual machines. Our results demonstrate that Shuttle can correctly address all necessary inter-application interactions while providing good isolation capability for all sample applications on different versions of Windows OS.

Cost-Driven Optimization of Cloud Resource Allocation for Elastic Processes

Today's extensive business process landscapes make it necessary to handle the execution of a large number of business processes and individual process steps. Especially if process steps require the invocation of resource-intensive applications or a large number of applications need to be executed concurrently, process owners may have to allocate extensive computational resources, leading to high fixed cost. In the work at hand, we propose an alternative to the provision of fixed resources, based on automatic leasing and releasing of Cloud-based computational resources. For this, we present an integrated approach which addresses the cost-driven optimization of Cloud-based computational resources for business processes in order to realize so-called Elastic Processes. Through an evaluation, we show the practical applicability and benefits of our contributions. Specifically, we find that our approach substantially reduces the cost compared to an ad hoc approach.

JETS: Language and System Support for Many-Parallel-Task Workflows

Many-task computing is a well-established paradigm for implementing loosely coupled applications (tasks) on large-scale computing systems. However, few of the model’s existing implementations provide efficient, low-latency support for executing tasks that are tightly coupled multiprocessing applications. Thus, a vast array of parallel applications cannot readily be used effectively within many-task workloads. In this work, we present JETS, a middleware component that provides high performance support for many-parallel-task computing (MPTC). JETS is based on a highly concurrent approach to parallel task dispatch and on new capabilities now available in the MPICH2 MPI implementation and the ZeptoOS Linux operating system. JETS represents an advance over the few known examples of multilevel many-parallel-task scheduling systems: it more efficiently schedules and launches many short-duration parallel application invocations; it overcomes the challenges of coupling the user processes of each multiprocessing application invocation via the messaging fabric; and it concurrently manages many application executions in various stages. We report here on the JETS architecture and its performance on both synthetic benchmarks and an MPTC application in molecular dynamics.

Facilitating inter-application interactions for OS-level virtualization

OS-level virtualization generates a minimal start-up and run-time overhead on the host OS and thus suits applications that require both good isolation and high efficiency. However, multiple-member applications required for forming a system may need to occasionally communicate across this isolation barrier to cooperate with each other while they are separated in different VMs to isolate intrusion or fault. Such application scenarios are often critical to enterprise-class servers, HPC clusters and intrusion/fault-tolerant systems, etc. We make the first effort to support the inter-application interactions in an OS-level virtualization system without causing a significant compromise on VM isolation. We identify all interactive operations that impact inter-application interactions, including inter-process communications, application invocations, resource name transfers and application dependencies. We propose Shuttle, a novel approach for facilitating inter-application interactions within and across OS-level virtual machines. Our results demonstrate that Shuttle can correctly address all necessary inter-application interactions while providing good isolation capability to all sample applications on different versions of Windows OS.

A precise definition of QoS for web services and its application in the invocation of applications from a workflow

The Workflow Reference Model standardizes workflow application development, in order to achieve the interoperability of different workflows. The web services technology allows optimizing the invocation of applications from the workflow engine, so that the workflow engine does not need to know the location of the application to invoke, and that any application can be relocated without involving a change in its invocation. But UDDI, the protocol used to register and locate web services, has some problems in establishing the correspondence between requester requirements and the specifying of services that have the same semantic behavior, even with different syntactic description. Furthermore, in the selection of a web service their quality attributes (QoS) are not considered. This proposal applies to the case study OpenUP/Basic, focusing on the quality attributes of web services for optimal selection and invocation.

Swift: A language for distributed parallel scripting

Scientists, engineers, and statisticians must execute domain-specific application programs many times on large collections of file-based data. This activity requires complex orchestration and data management as data is passed to, from, and among application invocations. Distributed and parallel computing resources can accelerate such processing, but their use further increases programming complexity. The Swift parallel scripting language reduces these complexities by making file system structures accessible via language constructs and by allowing ordinary application programs to be composed into powerful parallel scripts that can efficiently utilize parallel and distributed resources. We present Swift’s implicitly parallel and deterministic programming model, which applies external applications to file collections using a functional style that abstracts and simplifies distributed parallel execution.

Persistence in dynamic code transformation systems

Dynamic code transformation systems (DCTS) can broadly be grouped into three distinct categories: optimization, translation and instrumentation. All of these face the critical challenge of minimizing the overhead incurred during transformation since their execution is interleaved with the execution of the application itself. The common DCTS tasks incurring overhead are the identification of frequently executed code sequences, costly analysis of program information, and run-time creation (writing) of new code sequences. The cost of such work is amortized by the repeated execution of the transformed code. However, as these steps are applied to all general code regions (regardless of their execution frequency and characteristics), there is substantial overhead that impacts the application's performance. As such, it is challenging to effectively deploy dynamic transformation under fixed performance constraints. This paper explores a technique for eliminating the overhead incurred by exploiting persistent application execution characteristics that are shared across different application invocations. This technique is implemented and evaluated in Pin, a dynamic instrumentation engine. This version of Pin is referred to as Persistent Pin (PPin). Initial PPin experimental results indicate that using information from prior runs can reduce dynamic instrumentation overhead of SPEC applications by as much as 25% and over 90% for everyday applications like web browsers, display rendering systems, and spreadsheet programs.

GrADSolve—a grid-based RPC system for parallel computing with application-level scheduling

Although some existing Remote Procedure Call (RPC) systems provide support for remote invocation of parallel applications, these RPC systems lack powerful scheduling methodologies for the dynamic selection of resources for the execution of parallel applications. Some RPC systems support parallel execution of software routines with simple modes of parallelism. Some RPC systems statically choose the configuration of resources for parallel execution even before the parallel routines are invoked remotely by the end user. These policies of the existing systems prevent them from being used for remotely solving computationally intensive parallel applications over dynamic computational Grid environments. In this paper, we discuss a RPC system called GrADSolve that supports execution of parallel applications over Grid resources. In GrADSolve, the resources used for the execution of parallel application are chosen dynamically based on the load characteristics of the resources and the characteristics of the application. Application-level scheduling is employed for taking into account both the application and resource properties. GrADSolve also stages the user's data to the end resources based on the data distribution used by the end application. Finally, GrADSolve allows the users to store execution traces for problem solving and use the traces for subsequent solutions. Experiments are presented to prove that GrADSolve's data staging mechanisms can significantly reduce the overhead associated with data movement in current RPC systems. Results are also presented to demonstrate the usefulness of utilizing the execution traces maintained by GrADSolve for problem solving.