12,044 research outputs found

    Is XML-based test case prioritization for validating WS-BPEL evolution effective in both average and adverse scenarios?

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    In real life, a tester can only afford to apply one test case prioritization technique to one test suite against a service-oriented workflow application once in the regression testing of the application, even if it results in an adverse scenario such that the actual performance in the test session is far below the average. It is unclear whether the factors of test case prioritization techniques known to be significant in terms of average performance can be extrapolated to adverse scenarios. In this paper, we examine whether such a factor or technique may consistently affect the rate of fault detection in both the average and adverse scenarios. The factors studied include prioritization strategy, artifacts to provide coverage data, ordering direction of a strategy, and the use of executable and non-executable artifacts. The results show that only a minor portion of the 10 studied techniques, most of which are based on the iterative strategy, are consistently effective in both average and adverse scenarios. To the best of our know-ledge, this paper presents the first piece of empirical evidence regarding the consistency in the effectiveness of test case prioritization techniques and factors of service-oriented workflow applications between average and adverse scenarios.published_or_final_versio

    A subsumption hierarchy of test case prioritization for composite services

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    Autonomic care platform for optimizing query performance

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    Background: As the amount of information in electronic health care systems increases, data operations get more complicated and time-consuming. Intensive Care platforms require a timely processing of data retrievals to guarantee the continuous display of recent data of patients. Physicians and nurses rely on this data for their decision making. Manual optimization of query executions has become difficult to handle due to the increased amount of queries across multiple sources. Hence, a more automated management is necessary to increase the performance of database queries. The autonomic computing paradigm promises an approach in which the system adapts itself and acts as self-managing entity, thereby limiting human interventions and taking actions. Despite the usage of autonomic control loops in network and software systems, this approach has not been applied so far for health information systems. Methods: We extend the COSARA architecture, an infection surveillance and antibiotic management service platform for the Intensive Care Unit (ICU), with self-managed components to increase the performance of data retrievals. We used real-life ICU COSARA queries to analyse slow performance and measure the impact of optimizations. Each day more than 2 million COSARA queries are executed. Three control loops, which monitor the executions and take action, have been proposed: reactive, deliberative and reflective control loops. We focus on improvements of the execution time of microbiology queries directly related to the visual displays of patients' data on the bedside screens. Results: The results show that autonomic control loops are beneficial for the optimizations in the data executions in the ICU. The application of reactive control loop results in a reduction of 8.61% of the average execution time of microbiology results. The combined application of the reactive and deliberative control loop results in an average query time reduction of 10.92% and the combination of reactive, deliberative and reflective control loops provides a reduction of 13.04%. Conclusions: We found that by controlled reduction of queries' executions the performance for the end-user can be improved. The implementation of autonomic control loops in an existing health platform, COSARA, has a positive effect on the timely data visualization for the physician and nurse

    An Adaptive Mediation Framework for Workflow Management in the Internet of Things

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    Tärkavad värkvõrksüsteemid koosnevad arvukast hulgast heterogeensetest füüsilistest seadmetest, mis ühenduvad Internetiga. Need seadmed suudavad pidevalt ümbritseva keskkonnaga suhelda ja osana lõppkasutaja rakendusestest edendada valdkondi nagu tark kodu, e-tervis, logistika jne. Selleks, et integreerida füüsilisi seadmeid värkvõrgu haldussüssteemidega, on töövoo haldussüsteemid kerkinud esile sobiva lahendusena. Ent töövoo haldussüsteemide rakendamine värkvõrku toob kaasa reaalajas teenuste komponeerimise väljakutseid nagu pidev teenusavastus ja -käivitus. Lisaks kerkib küsimus, kuidas piiratud resurssidega värkvõrgu seadmeid töövoo haldussüsteemidega integreerida ning kuidas töövooge värkvõrgu seadmetel käivitada. Tööülesanded (nagu pidev seadmeavastus) võivad värkvõrgus osalevatele piiratud arvutusjõudluse ja akukestvusega seadmetele nagu nutitelefonid koormavaks osutuda. Siinkohal on võimalikuks lahenduseks töö delegeerimine pilve. Käesolev magistritöö esitleb kontekstipõhist raamistikku tööülesannete vahendamiseks värkvõrgurakendustes. Antud raamistikus modelleeritakse ning käitatakse tööülesandeid kasutades töövoogusid. Raamistiku prototüübiga läbi viidud uurimus näitas, et raamistik on võimeline tuvastama, millal seadme avastusülesannete pilve delegeerimine on kuluefektiivsem. Vahel aga pole töövoo käitamistarkvara paigaldamine värkvõrgu seadmetele soovitav, arvestades energiasäästlikkust ning käituskiirust. Käesolev töö võrdles kaht tüüpi töövookäitust: a) töövoo mudeli käitamine käitusmootoriga ning b) töövoo mudelist tõlgitud programmikoodi käitamine. Lähtudes katsetest päris seadmetega, võrreldi nimetatud kahte meetodit silmas pidades süsteemiressursside- ning energiakasutust.Emerging Internet of Things (IoT) systems consist of great numbers of heterogeneous physical entities that are interconnected via the Internet. These devices can continuously interact with the surrounding environment and be used for user applications that benefit human life in domains such as assisted living, e-health, transportation etc. In order to integrate the frontend physical things with IoT management systems, Workflow Management Systems (WfMS) have gained attention as a viable option. However, applying WfMS in IoT faces real-time service composition challenges such as continuous service discovery and invocation. Another question is how to integrate resource-contained IoT devices with the WfMS and execute workflows on the IoT devices. Tasks such as continuous device discovery can be taxing for IoT-involved devices with limited processing power and battery life such as smartphones. In order to overcome this, some tasks can be delegated to a utility Cloud instance. This thesis proposes a context-based framework for task mediation in Internet of Things applications. In the framework, tasks are modelled and executed as workflows. A case study carried out with a prototype of the framework showed that the proposed framework is able to decide when it is more cost-efficient to delegate discovery tasks to the cloud. However, sometimes embedding a workflow engine in an IoT device is not beneficial considering agility and energy conservation. This thesis compared two types of workflow execution: a) execution of workflow models using an embedded workflow engine and b) execution of program code translations based on the workflow models. Based on experiments with real devices, the two methods were compared in terms of system resource and energy usage

    Reference Exascale Architecture (Extended Version)

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    While political commitments for building exascale systems have been made, turning these systems into platforms for a wide range of exascale applications faces several technical, organisational and skills-related challenges. The key technical challenges are related to the availability of data. While the first exascale machines are likely to be built within a single site, the input data is in many cases impossible to store within a single site. Alongside handling of extreme-large amount of data, the exascale system has to process data from different sources, support accelerated computing, handle high volume of requests per day, minimize the size of data flows, and be extensible in terms of continuously increasing data as well as an increase in parallel requests being sent. These technical challenges are addressed by the general reference exascale architecture. It is divided into three main blocks: virtualization layer, distributed virtual file system, and manager of computing resources. Its main property is modularity which is achieved by containerization at two levels: 1) application containers - containerization of scientific workflows, 2) micro-infrastructure - containerization of extreme-large data service-oriented infrastructure. The paper also presents an instantiation of the reference architecture - the architecture of the PROCESS project (PROviding Computing solutions for ExaScale ChallengeS) and discusses its relation to the reference exascale architecture. The PROCESS architecture has been used as an exascale platform within various exascale pilot applications. This paper also presents performance modelling of exascale platform with its validation

    Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

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    With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00
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