Kassian Plankensteiner

GroudSim: an event-based simulation framework for computational grids and clouds

We present GroudSim, a Grid and Cloud simulation toolkit for scientific applications based on a scalable simulation-independent discrete-event core. GroudSim provides a comprehensive set of features for complex simulation scenarios from simple job executions on leased computing resources to calculation of costs, and background load on resources. Simulations can be parameterised and are easily extendable by probability distribution packages for failures which normally occur in complex environments. Experimental results demonstrate the improved scalability of GroudSim compared to a related process-based approach.

Fine-Grain Interoperability of Scientific Workflows in Distributed Computing Infrastructures

Today there exist a wide variety of scientific workflow management systems, each designed to fulfill the needs of a certain scientific community. Unfortunately, once a workflow application has been designed in one particular system it becomes very hard to share it with users working with different systems. Portability of workflows and interoperability between current systems barely exists. In this work, we present the fine-grained interoperability solution proposed in the SHIWA European project that brings together four representative European workflow systems: ASKALON, MOTEUR, WS-PGRADE, and Triana. The proposed interoperability is realised at two levels of abstraction: abstract and concrete. At the abstract level, we propose a generic Interoperable Workflow Intermediate Representation (IWIR) that can be used as a common bridge for translating workflows between different languages independent of the underlying distributed computing infrastructure. At the concrete level, we propose a bundling technique that aggregates the abstract IWIR representation and concrete task representations to enable workflow instantiation, execution and scheduling. We illustrate case studies using two real-workflow applications designed in a native environment and then translated and executed by a foreign workflow system in a foreign distributed computing infrastructure.

A New Fault Tolerance Heuristic for Scientific Workflows in Highly Distributed Environments Based on Resubmission Impact

Even though highly distributed environments such as Clouds and Grids are increasingly used for e-Science high performance applications, they still cannot deliver the robustness and reliability needed for widespread acceptance as ubiquitous scientific tools. To overcome this problem, existing systems resort to fault tolerance mechanisms such as task replication and task resubmission. In this paper we propose a new heuristic called Resubmission Impact to enhance the fault tolerance support for scientific workflows in highly distributed systems. In contrast to related approaches, our method can be used effectively on systems even in the absence of historic failure trace data. Simulated experiments of three real scientific workflows in the Austrian Grid environment show that our algorithm drastically reduces the resource waste compared to conservative task replication and resubmission techniques, while having a comparable execution performance and only a slight decrease in the success probability.

IWIR: a language enabling portability across grid workflow systems

Today there are many different scientific Grid workflow management systems using a wide array of custom workflow languages. Some of them are geared towards a data-based view, some are geared towards a control-flow based view and others try to be as generic, and therefore often complex, as possible. All of these languages and custom workflow management system front-ends fulfill special needs and workflow creation paradigms for their respective user communities. The problem is that once a workflow application has been created in one of these systems, it becomes very hard to share the workflow with users working with different systems. Portability and interoperability between current systems barely exists. In this work, we present a common workflow language for use as an intermediate exchange representation by multiple workflow systems. It comprises atomic tasks, compound tasks including conditionals, sequential and parallel loops as well as an expressive set of data types and data flow constructs.

Meeting Soft Deadlines in Scientific Workflows Using Resubmission Impact

We propose a new heuristic called Resubmission Impact to support fault tolerant execution of scientific workflows in heterogeneous parallel and distributed computing environments. In contrast to related approaches, our method can be effectively used on new or unfamiliar environments, even in the absence of historical executions or failure trace models. On top of this method, we propose a dynamic enactment and rescheduling heuristic able to execute workflows with a high degree of fault tolerance, while taking into account soft deadlines. Simulated experiments of three real-world workflows in the Austrian Grid demonstrate that our method significantly reduces the resource waste compared to conservative task replication and resubmission techniques, while having a comparable makespan and only a slight decrease in the success probability. On the other hand, the dynamic enactment method manages to successfully meet soft deadlines in faulty environments in the absence of historical failure trace information or models.

Integration of an event-based simulation framework into a scientific workflow execution environment for Grids and clouds

The utilisation of Grid and Cloud-based computing environments for solving scientific problems has become an increasingly used practice in the last decade. To ease the use of these global distributed resources, sophisticated middleware systems have been developed, enabling the transparent execution of applications by hiding low-level technology details from the user. The ASKALON environment is such a system, which supports the development and execution of distributed applications such as scientific workflows or parameter studies in Grid and Cloud computing environments. On the other hand, simulation is a widely accepted approach to analyse and further optimise the behaviour of software systems. Beside the advantage of enabling repeatable deterministic evaluations, simulations are able to circumvent the difficulties in setting up and operating multi-institutional Grid systems, thus providing a lightweight simulated distributed environment on a single machine. In this paper, we present the integration of the GroudSim Grid and Cloud event-based simulator into the ASKALON environment. This enables system, application developers, and users to perform simulations using their accustomed environment, thereby benefiting from the combination of an established real-world platform and the advantages of a simulation.

Fault Detection, Prevention and Recovery in Current Grid Workflow Systems

The workflow paradigm is a highly successful paradigm for the creation of Grid applications. Despite the popularity of the workflow approach, the systems that support the execution of workflow applications in Grid environments are still not able to deliver the quality, robustness and reliability that their users require and demand. To understand the current state-of-the-art and the reasons behind the shortcomings, we sent out a detailed questionnaire to developers of many of the major Grid workflow systems. This paper shows the outcome of the questionnaire evaluation, reveals future directions and helps to guide research towards the identified open issues in adoption of fault tolerance techniques.

Scheduling scientific workflows to meet soft deadlines in the absence of failure models

Highly distributed systems such as Clouds and Grids are used to execute complex scientific workflow applications by researchers from various areas of science. While scientists rightfully expect efficient and reliable execution of their applications, current systems often cannot deliver the required Quality of Service. We propose a dynamic execution and scheduling heuristic able to schedule workflow applications with a high degree of fault tolerance, while taking into account soft deadlines. Experimental results show that our method meets soft deadlines in volatile highly distributed systems in the absence of historic failure trace data or complex failure models of the target system.

Performance analysis of Grid applications in the ASKALON environment

In this paper we describe the approach taken by the ASKALON Grid application development and computing environment for scalability and overhead analysis of scientific applications in the Austrian Grid. We present a technique imported from parallel processing for overhead and scalability analysis of Grid applications based on speedup and efficiency metrics required primarily for tuning the middleware services and improving the executions. We present experimental results that validate our techniques for five real-world applications in the Austrian Grid environment.