Generic access to symbolic computing services

Symbolic computation is one of the computational domains that requires large computational resources. Computer Algebra Systems (CAS), the main tools used for symbolic computations, are mainly designed to be used as software tools installed on standalone machines that do not provide the required resources for solving large symbolic computation problems. In order to support symbolic computations an infrastructure built upon massively distributed computational environments must be developed. Building an infrastructure for symbolic computations requires a thorough analysis of the most important requirements raised by the symbolic computation world and must be built based on the most suitable architectural styles and technologies. The architecture that we propose is composed of several main components: the Computer Algebra System (CAS) Server that exposes the functionality implemented by one or more supporting CASs through generic interfaces of Grid Services; the Architecture for Grid Symbolic Services Orchestration (AGSSO) Server that allows seamless composition of CAS Server capabilities; and client side libraries to assist the users in describing workflows for symbolic computations directly within the CAS environment. We have also designed and developed a framework for automatic data management of mathematical content that relies on OpenMath encoding. To support the validation and fine tuning of the system we have developed a simulation platform that mimics the environment on which the architecture is deployed

Supporting Quality of Service in Scientific Workflows

While workflow management systems have been utilized in enterprises to support businesses for almost two decades, the use of workflows in scientific environments was fairly uncommon until recently. Nowadays, scientists use workflow systems to conduct scientific experiments, simulations, and distributed computations. However, most scientific workflow management systems have not been built using existing workflow technology; rather they have been designed and developed from scratch. Due to the lack of generality of early scientific workflow systems, many domain-specific workflow systems have been developed. Generally speaking, those domain-specific approaches lack common acceptance and tool support and offer lower robustness compared to business workflow systems. In this thesis, the use of the industry standard BPEL, a workflow language for modeling business processes, is proposed for the modeling and the execution of scientific workflows. Due to the widespread use of BPEL in enterprises, a number of stable and mature software products exist. The language is expressive (Turingcomplete) and not restricted to specific applications. BPEL is well suited for the modeling of scientific workflows, but existing implementations of the standard lack important features that are necessary for the execution of scientific workflows. This work presents components that extend an existing implementation of the BPEL standard and eliminate the identified weaknesses. The components thus provide the technical basis for use of BPEL in academia. The particular focus is on so-called non-functional (Quality of Service) requirements. These requirements include scalability, reliability (fault tolerance), data security, and cost (of executing a workflow). From a technical perspective, the workflow system must be able to interface with the middleware systems that are commonly used by the scientific workflow community to allow access to heterogeneous, distributed resources (especially Grid and Cloud resources). The major components cover exactly these requirements: Cloud Resource Provisioner Scalability of the workflow system is achieved by automatically adding additional (Cloud) resources to the workflow system’s resource pool when the workflow system is heavily loaded. Fault Tolerance Module High reliability is achieved via continuous monitoring of workflow execution and corrective interventions, such as re-execution of a failed workflow step or replacement of the faulty resource. Cost Aware Data Flow Aware Scheduler The majority of scientific workflow systems only take the performance and utilization of resources for the execution of workflow steps into account when making scheduling decisions. The presented workflow system goes beyond that. By defining preference values for the weighting of costs and the anticipated workflow execution time, workflow users may influence the resource selection process. The developed multiobjective scheduling algorithm respects the defined weighting and makes both efficient and advantageous decisions using a heuristic approach. Security Extensions Because it supports various encryption, signature and authentication mechanisms (e.g., Grid Security Infrastructure), the workflow system guarantees data security in the transfer of workflow data. Furthermore, this work identifies the need to equip workflow developers with workflow modeling tools that can be used intuitively. This dissertation presents two modeling tools that support users with different needs. The first tool, DAVO (domain-adaptable, Visual BPEL Orchestrator), operates at a low level of abstraction and allows users with knowledge of BPEL to use the full extent of the language. DAVO is a software that offers extensibility and customizability for different application domains. These features are used in the implementation of the second tool, SimpleBPEL Composer. SimpleBPEL is aimed at users with little or no background in computer science and allows for quick and intuitive development of BPEL workflows based on predefined components

A Framework for Model-Driven Scientific Workflow Engineering

So-called scientific workflows are one important means in the context of data-intensive science for reliable and efficient scientific data processing in distributed computing infrastructures such as Grids. Scientific Workflow Management Systems (SWfMS) help scientists model and run scientific workflows, whereas a domain-specific layer for workflow modeling by a scientist and a technical layer for automated workflow execution can be distinguished. Initially, many SWfMS were developed from scratch using custom workflow technologies languages without application of already existing and established business workflow technologies. Among the reasons were different life cycles for scientific and business workflows as well as incompatible interfaces and communication protocols of the respective execution infrastructures. Meanwhile, several business IT infrastructures have evolved to serviceoriented architectures (SOAs), for which many Web service standards and technologies have been developed. The Web Services Business Process Execution Language (BPEL), for example, is a well-accepted standard for the implementation and execution of business workflows in SOAs. The SOA architecture pattern has been adopted in scientific IT infrastructures by so-called Service Grids based on existing standards and technologies. Due to this development, BPEL is also suitable for the execution of scientific workflows at the technical layer, which has been elaborated on in many publications and projects. However, BPEL is a workflow language for IT experts and is originally not suited for scientific workflow modeling by a scientist at the domain-specific layer. A domain-specific abstraction of BPEL is therefore required that can be specifically tailored for scientific workflow modeling as well as a corresponding mapping to the technical layer. These challenges of the domain-specific abstraction and the mapping are addressed in this thesis with the help of the Business Process Model and Notation (BPMN) standard and technologies from Model-Driven Software Development (MDSD). Therefore, the MoDFlow approach for Model-Driven Scientific WorkFlow Engineering is presented to map domain-specific scientific workflow models via a BPMN-based intermediate layer to an executable workflow model. The intermediate layer is specified by MoDFlow.BPMN, which is a BPMN metamodel subset with custom extensions for the scientific domain. MoDFlow.BPMN2BPEL defines three consecutive transformation steps to map MoDFlow.BPMN to BPEL for workflow execution. Furthermore, different methods to utilize and extend MoDFlow.BPMN and MoDFlow.BPMN2BPEL are described in the MoDFlow approach, in which the definition of so-called domain-specific languages (DSLs) for the modeling of scientific workflows at the domain-specific layer is focused. The MoDFlow framework is an implementation of the MoDFlow approach, which is based on the Eclipse Modeling Framework (EMF). The MoDFlow framework is evaluated in three application scenarios, in which different utilization and extension mechanisms are examined. The first two application scenarios investigate the technical feasibility of the approach and support scientific workflows with parameter sweeps that are executed on a Grid infrastructure. The third application scenario has been conducted in collaboration with the PubFlow project, which aims to create an infrastructure to model and execute data publication workflows. Based on the Xtext framework, a textual DSL and a corresponding language infrastructure is defined for this purpose that supports developers in creating data publication workflows. This scenario aims to illustrate the practicability of the MoDFlow framework. PubFlow currently plans to implement an additional graphical DSL based on the BPMN notation and a corresponding workflow editor for scientists

The OMII Software Distribution

This paper describes the work carried out at the Open Middleware Infrastructure Institute (OMII) and the key elements of the OMII software distribution that have been developed in collaboration with members of the Managed Programme Initiative. The main objective of the OMII is to preserve and consolidate the achievements of the UK e-Science Programme by collecting, maintaining and improving the software modules that form the key components of a generic Grid middleware. Recently, the activity at Southampton has been extended beyond 2009 through a new project, OMII-UK, that forms a partnership that now includes the OGSA-DAI activities at Edinburgh and the myGrid project at Manchester

CaGrid Workflow Toolkit: A taverna based workflow tool for cancer grid

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Cloud Computing and Grid Computing 360-Degree Compared

Cloud Computing has become another buzzword after Web 2.0. However, there are dozens of different definitions for Cloud Computing and there seems to be no consensus on what a Cloud is. On the other hand, Cloud Computing is not a completely new concept; it has intricate connection to the relatively new but thirteen-year established Grid Computing paradigm, and other relevant technologies such as utility computing, cluster computing, and distributed systems in general. This paper strives to compare and contrast Cloud Computing with Grid Computing from various angles and give insights into the essential characteristics of both.Comment: IEEE Grid Computing Environments (GCE08) 200

Designing a Resource Broker for Heterogeneous Grids

Grids provide uniform access to aggregations of heterogeneous resources and services such as computers, networks and storage owned by multiple organizations. However, such a dynamic environment poses many challenges for application composition and deployment. In this paper, we present the design of the Gridbus Grid resource broker that allows users to create applications and specify different objectives through different interfaces without having to deal with the complexity of Grid infrastructure. We present the unique requirements that motivated our design and discuss how these provide flexibility in extending the functionality of the broker to support different low-level middlewares and user interfaces. We evaluate the broker with different job profiles and Grid middleware and conclude with the lessons learnt from our development experience.Comment: 26 pages, 15 figure