Distributed Allocation of Workflow Tasks in MANETs

Fine-grained hardware protection could provide a powerful and effective means for isolating untrusted code. However, previous techniques for providing fine-grained protection in hardware have lead to poor performance. Legba has been proposed as a new caching architecture, designed to reduce the granularity of protection, without slowing down the processor. Unfortunately, the designers of Legba have not attempted an implementation. Instead, all of their analysis is based purely on simulations. We present an implementation of the Legba design on a MIPS Core Processor, along with an analysis of our observations and results. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Implementing Legba: Fine-Grained Memory Protection Aaron Sheffield, Ross T. Sowell, Mike Wilson Department of Computer Science & Engineering Washington University in St. Louis One Brookings Drive, Campus Box 1045 St. Louis, Missouri 63130-4899 {ajs6, mlw2}@cec.wustl.edu rsowell@gmail.com Abstract—Fine-grained hardware protection could provide a powerful and effective means for isolating untrusted code. However, previous techniques for providing fine-grained protection in hardware have lead to poor performance. Legba has been proposed as a new caching architecture, designed to reduce the granularity of protection, without slowing down the processor. Unfortunately, the designers of Legba have not attempted an implementation. Instead, all of their analysis is based purely on simulations. We present an implementation of the Legba design on a MIPS Core Processor, along with an analysis of our observations and results.Fine-grained hardware protection could provide a powerful and effective means for isolating untrusted code. However, previous techniques for providing fine-grained protection in hardware have lead to poor performance. Legba has been proposed as a new caching architecture, designed to reduce the granularity of protection, without slowing down the processor. Unfortunately, the designers of Legba have not attempted an implementation. Instead, all of their analysis is based purely on simulations. We present an implementation of the Legba design on a MIPS Core Processor, along with an analysis of our observations and results.

Identification of groups of functionally related genes from high throughput gene expression data is an important step towards elucidating gene functions at a global scale. Most existing approaches treat gene expression data as points in a metric space, and apply conventional clustering algorithms to identify sets of genes that are close to each other in the metric space. However, they usually ignore the topology of the underlying biological networks. In this paper, we propose a network-based clustering method that is biologically more realistic. Given a gene expression data set, we apply a rank-based transformation to obtain a sparse co-expression network, and use a novel spectral clustering algorithm to identify natural community structures in the network, which correspond to gene functional modules. We have tested the method on two large-scale gene expression data sets in yeast and Arabidopsis, respectively. The results show that the clusters identified by our method on these datasets are functionally richer and more coherent than the clusters from the standard k-means clustering algorithm. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Discovering Functional Modules by Clustering Gene Co-expression Networks Jianhua Ruan and Weixiong Zhang Department of Computer Science and Department of Genetics Washington University in St. Louis, St. Louis, MO 63130, USA jruan@cse.wustl.edu, zhang@cse.wustl.edu

Service provisioning has gained significant attention as a promising programming model for heterogeneous wireless sensor networks. Its key idea is to exploit the decoupling of service providers and consumers to enable platform-independent applications that are dynamically bound to platform-specific services. We explore novel adaptive service binding strategies that are able to cope with network dynamics and to promote energy conservation. To achieve this goal, we developed policies and algorithms that automatically switch providers in response to network topology changes and adapt application behavior when opportunities for energy savings surface. The latter is accomplished by providing limited information about the energy consumption associated with using various services, by systematically exploiting opportunities for sharing service invocations, and by exploiting the broadcast nature of wireless communication in WSNs. The policies and algorithms have been implemented and evaluated on two disparate WSN platforms, the TelosB and Imote2. Empirical results show that adaptive service provisioning can significantly increase service availability and enable energy-aware service binding decisions that result in increased energy efficiency, while imposing minimal additional burden on the application, service, and device developers. Applications involving medical patient monitoring and structural health monitoring are used in the evaluation process. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Adaptive Service Provisioning for Wireless Sensor Networks Chien-Liang Fok, Gruia-Catalin Roman and Chenyang Lu Washington University in St. Louis {liang, roman, lu}@cse.wustl.edu Abstract—Service provisioning has gained significant attention as a promising programming model for heterogeneous wireless sensor networks. Its key idea is to exploit the decoupling of service providers and consumers to enable platform-independent applications that are dynamically bound to platform-specific services. We explore novel adaptive service binding strategies that are able to cope with network dynamics and to promote energy conservation. To achieve this goal, we developed policies and algorithms that automatically switch providers in response to network topology changes and adapt application behavior when opportunities for energy savings surface. The latter is accomplished by providing limited information about the energy consumption associated with using various services, by systematically exploiting opportunities for sharing service invocations, and by exploiting the broadcast nature of wireless communication in WSNs. The policies and algorithms have been implemented and evaluated on two disparate WSN platforms, the TelosB and Imote2. Empirical results show that adaptive service provisioning can significantly increase service availability and enable energyaware service binding decisions that result in increased energy efficiency, while imposing minimal additional burden on the application, service, and device developers. Applications involving medical patient monitoring and structural health monitoring are used in the evaluation process, demonstrating the system’s efficacy.Service provisioning has gained significant attention as a promising programming model for heterogeneous wireless sensor networks. Its key idea is to exploit the decoupling of service providers and consumers to enable platform-independent applications that are dynamically bound to platform-specific services. We explore novel adaptive service binding strategies that are able to cope with network dynamics and to promote energy conservation. To achieve this goal, we developed policies and algorithms that automatically switch providers in response to network topology changes and adapt application behavior when opportunities for energy savings surface. The latter is accomplished by providing limited information about the energy consumption associated with using various services, by systematically exploiting opportunities for sharing service invocations, and by exploiting the broadcast nature of wireless communication in WSNs. The policies and algorithms have been implemented and evaluated on two disparate WSN platforms, the TelosB and Imote2. Empirical results show that adaptive service provisioning can significantly increase service availability and enable energyaware service binding decisions that result in increased energy efficiency, while imposing minimal additional burden on the application, service, and device developers. Applications involving medical patient monitoring and structural health monitoring are used in the evaluation process, demonstrating the system’s efficacy.

Protein databases have grown exponentially over the last decade. This exponential growth has made extracting valuable information from these databases increasingly time consuming. This project presents a new method of accelerating a commonly used program for performing similarity searching on protein databases, BLASTP. This project describes the design and implementation of Mercury BLASTP, a customized hardware accelerated variant of BLASTP. This project focuses on the gapped alignment stage of Mercury BLASTP and provides design details and implementation results. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Acceleration of Gapped Alignment in BLASTP Using the Mercury System Brandon Harris bbh2@wustl.edu Abstract Protein databases have grown exponentially over the last decade. This exponential growth has made extracting valuable information from these databases increasingly time consuming. This project presents a new method of accelerating a commonly used program for performing similarity searching on protein databases, BLASTP. This project describes the design and implementation of Mercury BLASTP, a customized hardware accelerated variant of BLASTP. This project focuses on the gapped alignment stage of Mercury BLASTP and provides design details and implementation results.Protein databases have grown exponentially over the last decade. This exponential growth has made extracting valuable information from these databases increasingly time consuming. This project presents a new method of accelerating a commonly used program for performing similarity searching on protein databases, BLASTP. This project describes the design and implementation of Mercury BLASTP, a customized hardware accelerated variant of BLASTP. This project focuses on the gapped alignment stage of Mercury BLASTP and provides design details and implementation results.

Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings. Type of Report: MS Project Report Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 EWA Model with Recency Effect and Limited Memory Hang Xie xiehang@go.wustl.edu Yixin Chen chen@cse.wustl.edu Washington University One Brookings Drive St. Louis, MO 63130 United States

The field of manifold learning provides powerful tools for parameterizing high-dimensional data points with a small number of parameters when this data lies on or near some manifold. Images can be thought of as points in some high-dimensional image space where each coordinate represents the intensity value of a single pixel. These manifold learning techniques have been successfully applied to simple image sets, such as handwriting data and a statue in a tightly controlled environment. However, they fail in the case of natural image sets, even those that only vary due to a single degree of freedom, such as a person walking or a heart beating. Parameterizing data sets such as these will allow for additional constraints on traditional computer vision problems such as segmentation and tracking. This dissertation explores the reasons why classical manifold learning algorithms fail on natural image sets and proposes new algorithms for parameterizing this type of data. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 WASHINGTON UNIVERSITY THE HENRY EDWIN SEVER GRADUATE SCHOOL DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING MANIFOLD LEARNING FOR NATURAL IMAGE SETS by Richard M. Souvenir, M.S. Computer Science, B.S. Applied Science Prepared under the direction of Professor Robert Pless A dissertation presented to the Henry Edwin Sever Graduate School of Washington University in partial fulfillment of the requirements for the degree of DOCTOR OF SCIENCE August 2006 Saint Louis, Missouri WASHINGTON UNIVERSITY THE HENRY EDWIN SEVER GRADUATE SCHOOL DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

Modern computer architectures have evolved from uni-processor platforms to multi-processor and multi-core platforms, but traditional real-time distributed middleware such as RT-CORBA has not kept pace with that evolution. To address those issues, this paper describes the design and implementation of MCFlow, a new real-time distributed middleware for dependent task graphs running on multi-core platforms. MCFlow provides the following contributions to the state of the art in real-time middleware: (1) it provides an efficient C++ based component model through which computations can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) it allows optimizations for inter-component communication to avoid data copying without sacrificing the parallel executability of data dependent tasks; (3) it strictly separates timing and functional concerns of an application so that they can evolve and can be configured independently; and (4) it provides a novel event dispatching architecture that uses lock free algorithms to avoid mutex locking and reduce memory contention, CPU context switching, and priority inversion. We also present an empirical evaluation that demonstrates the efficacy of our approach. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 The Design and Implementation of MCFlow: a Real-time Multi-core Aware Middleware for Dependent Task Graphs Huang-Ming Huang, Christopher Gill, Chengyang Lu Department of Computer Science and Engineering, Washington University St. Louis, MO, USA {hh1, cdgill, lu}@cse.wustl.edu Abstract—Modern computer architectures have evolved from uni-processor platforms to multi-processor and multi-core platforms, but traditional real-time distributed middleware such as RT-CORBA has not kept pace with that evolution. To address those issues, this paper describes the design and implementation of MCFlow, a new real-time distributed middleware for dependent task graphs running on multi-core platforms. MCFlow provides the following contributions to the state of the art in real-time middleware: (1) it provides an efficient C++ based component model through which computations can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) it allows optimizations for inter-component communication to avoid data copying without sacrificing the parallel executability of data dependent tasks; (3) it strictly separates timing and functional concerns of an application so that they can evolve and can be configured independently; and (4) it provides a novel event dispatching architecture that uses lock free algorithms to avoid mutex locking and reduce memory contention, CPU context switching, and priority inversion. We also present an empirical evaluation that demonstrates the efficacy of our approach.Modern computer architectures have evolved from uni-processor platforms to multi-processor and multi-core platforms, but traditional real-time distributed middleware such as RT-CORBA has not kept pace with that evolution. To address those issues, this paper describes the design and implementation of MCFlow, a new real-time distributed middleware for dependent task graphs running on multi-core platforms. MCFlow provides the following contributions to the state of the art in real-time middleware: (1) it provides an efficient C++ based component model through which computations can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) it allows optimizations for inter-component communication to avoid data copying without sacrificing the parallel executability of data dependent tasks; (3) it strictly separates timing and functional concerns of an application so that they can evolve and can be configured independently; and (4) it provides a novel event dispatching architecture that uses lock free algorithms to avoid mutex locking and reduce memory contention, CPU context switching, and priority inversion. We also present an empirical evaluation that demonstrates the efficacy of our approach. Keywords-component; middleware

Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an exact match of the 3’ adapter sequence. In this report, I investigated methodologies as well as the strengths and weaknesses of five representative mainstream adapter trimming tools in order to suggest a direction for other researchers. Furthermore, four sets of detailed analysis were performed to evaluate the performances of these tools. I demonstrated that my adapter trimming method is flexible, accurate and efficient for Next Generation Sequencing (NGS) analysis. Type of Report: MS Project Report Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Master’s Project Report LCScanner: An Efficient and Accurate Trimming Tool for Illumina Next Generation Sequencing Reads by Xiang Zhou Master of Engineering in Computer Science Washington University in St. Louis, 2012 Research Advisor: Professor Weixiong Zhang

Many scientific endeavors, such as molecular biology, have become dependent on big data and its analysis. For example, precision medicine depends on molecular measurements and data analysis per patient. Data analyses supporting medical decisions must be standardized and performed consistently across patients. While perhaps not life-threatening, data analyses in basic research have become increasingly complex. RNAseq data, for example, entails a multi-step analysis ranging from quality assessment of the measurements to statistical analyses. Workflow management systems (WFMS) enable the development of data analysis workflows (WF), their reproduction, and their application to datasets of the same type. However, far more than a hundred WFMS are available, and there is no way to convert data analysis WFs among WFMS. Therefore, the initial choice of a WFMS is important as it entails a lockin to the system. The reach in their particular field (number of citations) can be used as a proxy for selecting a WFMS, but of the about 25 WFMS we mention in this work, at least 5 have a large reach in scientific data analysis. Hence other criteria are needed to delineate among WFMS. By extracting such criteria from selected studies concerning WFMS and adding additional criteria, we arrived at five critical criteria: reproducibility, reusability, FAIRness, versioning support, and security. Another five criteria (providing a graphical user interface, WF flexibility, WF scalability, WF shareability, and computational transparency) we deemed important but not critical for the assessment of WFMS. We applied the criteria to the most cited WFMS in PubMed and found none that support all criteria. We hope that suggesting these criteria will spark a discussion on what features are important for WFMS in scientific data analysis and may lead to developing WFMS that fulfill such criteria.

Information System is one of the key domain in which lot of research has been done in the past few years. Applying Information systems to heterogeneous and distributed environments is one of the current research areas. Business Process Management Systems is the information systems which deal with the administration of tasks in the business processes, organizational structures, or in the related context. The Workflow Management system, the early idea of BPM, controls the workflow in an organization, data transfer, and integration of legacy information systems with existing programs and program modules, delegation of business tasks. Offering task management services especially modeling of business processes and underlying organizations, BPM serves it meaning and incorporates the WFM system. BPM supporting the use of knowledge concerning the awareness/unawareness of integrated software, and analysis of processes and organizational structure in terms of verification, modification, evaluation are key management in BPM system I.INTRODUCTION TO BPM: Combination of corporate restructuring and mergers urged the department and processes to be automated and linked together. Unfortunately it created largely disconnected spaghetti of systems and applications. Business Process Management (BPM) was born from a strong need to streamline internal processes and connections between both internal and external functions. It provides ability to model, monitor, manage and manipulate processes quickly in response to changes in strategy and market forces. BPM is an extension of classical Work Flow Management (WFM) systems and approaches. BPM delivers the maximum utility of legacy system. It is a method for revolutionizing the way the work moves throughout an organization. II.COMPONENTS OF BPM: The four key elements in Business Process Management are: Process modeling, Process rule, Process management, and Process performance analytics. Process modeling: Process modeling describes the flow of information (business process).It helps in building a model of process and mapping into an implementation frame work. Modeling requires a consistent analysis and representation of the processes. It forms the basis for the userspecific process environment. Process Rule: Process Rule is a heart of the BPM. It involves execution of discrete steps & integration of information. A process rules engine is used for this purpose. The engine is to monitor and manage the given steps by providing a flow control over the business process. If a process fails or delayed, a compensated action can be done to rectify. Process Management: Process Management is to correlate business/application events to fundamental business metrics .It enables the organization to monitor and optimize the business process. Once the process has been analyzed, modeled and the associated rules are formed. The next stage involves the visualization and management. Visualization means transaction data ranging from holistic to process-state or client state specific rules. Process Performance Analytics: Process Performance Analytics is a transition data source available for sophisticated management analytics .This data should be available on a retrospective or real-time basis. It should answer to one of the most difficult question like “how much does it cost to process a specific transaction?” By this way BPM mainly addresses four components. They are Work Flow Management, Content and records management Enterprise Application Integration (EAI) and Business Activity monitoring (BAM). III.RELEVENCE TO SYSTEM INTEGRATION: BPM can be fitted easily on the top of existing IT system. It is the Process rules that governs all the happenings and optimizes the process. BPM will not be able to work without the connectivity provided by the EAI layer. EAI layer provides BPM to gain and measure the value from the investment. On the other hand, BPM provides value to the EAI technology layer of Information technology. BPM layer offers business management the view of the message processing layer. It is used to unlock the value of the information held in the integration layer. It is also used to gather data of every transaction in the lifecycle. IV.APPLICATION OF BPM: BPM can be applied to any application which needs these advantages. BPM reduces unnecessary high losses in time critical transactions, helps to provide any critical information, practical application yield fast ROI ,better control over the information, identifying and maximizing the benefits faster, better analysis and tracking, provides enterprise-wide visibility of business processes, improve the effectiveness of the core operations, provides ability to coordinate interactions between information systems, business process and the people, flexible and easily changed by non-technical business people.

Structuring an organization around its business processes has many benefits for both the processes themselves as well as the workflow and business process management within an organization in general. However, there are many challenges that make such a transition from a classical hierarchic to a state-of-the-art process organization difficult. In particular, traditional departments often resist loss of autonomy within their organization and, thus, may prevent successful implementation of business process management techniques such as process-oriented workflow management systems. Therefore, this paper proposes a flexible workflow management system architecture consisting of multiple parts that can be replicated and distributed within an organization's private cloud network. Based on distributed components of a workflow management system, it supports both organizations with legacy organizational structures as well as those which require increased autonomy of their respective organizational units. As a result, this system allows, on the one hand side, to manage some organizational units independently and to regulate them in a distributed, process-driven way while, on the other, still allowing the overall organization to exploit many advantages of a centralized workflow management system. The resulting system is based on experiences of a DFG funded technology transfer project aiming at applying previous research results in autonomous business process management to practical needs and requirements of a real production system application.

Workflow management systems (WfMS) are designed to enable the enactment of business processes, i.e. to extract and maintain the process logic between business applications. Within a workflow management solution, heterogeneous applications are connected through a given workflow definition. Future development efforts must aim to establish interoperability between different WfMS. This leads straight to interoperability problems of two types: in a technical point of view, one WfMS has to be able to abstract from a concrete implementation (programming language, hardware, etc.) of another WfMS. In a semantic point of view, WfMS have to agree on the execution semantics of a workflow definition. We try to cope with the semantic interoperability problem by defining a workflow repository which enables extensible communication between WfMS. To understand the notion and the central function of repositories, a short history of metadata systems is given. Based on a modular architecture of WfMS, a repository is developed and sketched in a CORBA compliant style. This repository shows the expressiveness and the idea of extensibility of our interoperability approach.

Workflow technology has been adopted in scientific domains to orchestrate and automate scientific processes in order to facilitate experimentation. Such scientific workflows often involve large data sets and intensive computation that necessitate the use of the Grid, which offers supercomputing power through shared distributed resources. To execute a scientific workflow in the Grid, tasks within the workflow that represent steps in the scientific process are assigned to Grid resources for execution. To ensure efficient execution of the workflow, Grid workflow scheduling is required to manage the allocation of Grid resources. Although many Grid workflow scheduling techniques exist, they are mainly designed for the execution of a single workflow. This is not the case with parameter sweep workflows which focus on parametric study and parameter optimisation. A parameter sweep workflow is executed numerous times with different input parameters in order to determine the effect of each parameter combination on the experiment. While executing multiple instances of a parameter sweep workflow in parallel can reduce the time required for the overall execution, this execution introduces new challenges to Grid workflow scheduling. Not only is a scheduling algorithm that is able to manage multiple workflow instances required, but this algorithm also needs the ability to schedule tasks across multiple workflow instances judiciously, as tasks may require the same set of Grid resources. Without appropriate resource allocation, resource competition problem could arise. In the thesis, we propose a new Grid workflow scheduling technique for parameter sweep workflow called the Besom scheduling algorithm. The scheduling decision of our algorithm is based on the resource dependencies of tasks in the workflow, as well as conventional Grid resource-performance metrics. In addition, the proposed technique is extended to handle loop structures in scientific workflows without using existing loop-unrolling techniques. We evaluate the Besom algorithm under a variety of conditions. A comparison between the simulation results of the Besom algorithm and of the three existing Grid workflow scheduling algorithms shows that the Besom algorithm is able to perform better than the existing algorithms for workflows that have complex structures and that involve overlapping resource dependencies of tasks. The Besom scheduling algorithm advances the ability to schedule parallel execution of parameter sweep workflows in the Grid. The outcomes of this thesis justify continuing research in this area to increase our understanding of scheduling multiple Grid workflow instances and to provide support to those involved in parametric study and scientific workflow management.

Workflows are a technology to structure work in functional, non-overlapping steps. They define
\nnot only the order of execution of the steps, and describe whether steps are executed in
\nparallel, they also specify who or what tool has to fulfill which step. Workflows offer the possibility
\nto automate work, to increase the understandability of processes, and they ease the
\ncontrol of process execution. The tools to manage workflows, so called workflow management
\nsystems (WfMSs), are traditionally rigid as they separate workflow definition done at build time
\nfrom workflow execution done at run time. This makes them ill-suited for managing flexible and
\nunstructured workflows. In this thesis, we focus on the support of flexible processes in eHealth,
\nwhich are affected by more foreseen than unforeseen events. To bridge the gap between rigid
\nWfMSs and flexible workflows, we developed a concept for dynamic and context-aware workflow
\nmanagement called Flexwoman. Although our focus lies on flexible eHealth processes,
\nFlexwoman is a generic approach that can be applied to several different application domains.
\nFlexwoman supports the usage of context information to adapt processes automatically at run
\ntime to foreseen events. Processes can also be manually adapted to handle unforeseen events.
\nTo achieve this flexibility, context information from different sensors is unified and thus can be
\nanalyzed in the same way. The analysis and adaptation of workflows is executed with a rule engine.
\nA rule engine can store, reason about and apply knowledge automatically and efficiently.
\nRules and application logic are separated, thus, rules can be changed during run time without
\naffecting application logic or process description. Workflows are internally described by Hierarchical
\nColored Petri nets (HCPNs) and executed by a HCPN execution engine. HCPNs allow for
\na deterministic execution of workflows and can represent workflows on different levels of detail.
\nIn summary, in Flexwoman, significant context changes (events) trigger automated adaptations
\nthat replace parts of the workflow by sub workflows, which can in turn be adapted. The adaptations
\nand the rules for context-aware adaptation are saved in the organizational memory for
\nlater reuse. Flexwoman’s event based behavior facilitates proactive adaptations instead of only
\nallowing for adaptations while entering or leaving a task. Replacements are not bound to special
\nplaces defined at build time but each part of the workflow, which has not been executed yet, can
\nbe replaced at run time. We implemented and evaluated the concept. The evaluations show
\ni) that all required functionality is available, ii) that the system scales with a growing number of
\nrules, and iii) that the system correctly handles failure situations.

Scalability to large, heterogeneous, and distributed environments is an important requirement for workflow management systems (WfMS). As a consequence, the management of the configuration of a WfMS installation becomes a key issue. This paper proposes an approach for managing the configuration of WfMS together with an assignment strategy for workflow instances. Separating the logical issues of the workflow model from the physical configuration of a WfMS is the basis of our strategy. A formalization of physical organizational requirements in a WfMS configuration covering access rights, usage policies, and costs for the access to WfMS servers is presented and used in the assignment strategy for workflow instances. The results of our approach fit well for many existing WfMS and also for the reference architecture of the Workflow Management Coalition.