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Kropf, Peter

Nom
Kropf, Peter
Affiliation principale
Fonction
Professeur ordinaire
Email
peter.kropf@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/221

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  • Publication
    Restriction temporaire
  • Publication
    Accès libre
    THUNDERSTORM: A Tool to Evaluate Dynamic Network Topologies on Distributed Systems
    (2019-10-1)
    Liechti, Luca
    ;
    Gouveia, Paulo
    ;
    Neves, João
    ;
    Kropf, Peter 
    ;
    Matos, Miguel
    ;
    Schiavoni, Valerio 
    Abstract—Network dynamics, such as sudden changes in latency or available bandwidth, have a significant impact on the performance of distributed systems. While such dynamics are common, especially in WAN deployments, existing tools lack the capabilities to systematically evaluate the impact of such changes in real systems. We present THUNDERSTORM, a tool to evaluate the impact of dynamic network topologies on the performance of large-scale distributed systems. THUNDERSTORM is a fully functional tool that integrates with Kubernetes and can be used to evaluate off-the-shelf applications. THUNDERSTORM defines an easy-to-use language to describe arbitrarily complex network topologies and dynamic events used to enrich the default container composition descriptors. Our evaluation, using micro- and macro-benchmarks, as well as off-the-shelf unmodified systems (e.g., Apache Cassandra, MariaDB) shows that THUNDERSTORM is easy to use, accurate in reproducing dynamic behaviours and that it can help researchers uncover unexpected behaviours otherwise very costly to reproduce in real deployments typically captured only during malfunctioning periods.
  • Publication
    Métadonnées seulement
    Efficient Broadcasting Algorithm in Harary-like Networks}
    (2017-8-1)
    Bhabak, Puspal
    ;
    Harutyunyan, Hovhannes
    ;
    Kropf, Peter 
    In this paper, we analyze the properties of Harary graphs and some derivatives with respect to the achievable performance of communication within network structures based on these graphs. In particular we defined Cordal-Haray graphs on n nodes which can be constructed for any even n for any odd degree between 3 and 2[log n] - 1. We also present a simple algorithm for fast message broadcasting in this network. Our analysis show that when nodes of a Cordal-Harary Graph have logarithmic degree then the broadcasting time will be as small as [log n] which is the minimum possible value for a network on n nodes. All this properties show that Cordal-Harary is a very good network architecture for parallel processing.
  • Publication
    Métadonnées seulement
    A LRAAM-based Partial Order Function for Ontology Matching in the Context of Service Discovery
    (2017-6-14)
    Ludolph, Hendrik
    ;
    Babin, Gilbert
    ;
    Kropf, Peter 
    The demand for Software as a Service is heavily increasing in the era of Cloud. With this demand comes a proliferation of third-party service offerings to fulfill it. It thus becomes crucial for organizations to find and select the right services to be integrated into their existing tool landscapes. Ideally, this is done automatically and continuously. The objective is to always provide the best possible support to changing business needs. In this paper, we explore an artificial neural network implementation, an LRAAM, as the specific oracle to control the selection process. We implemented a proof of concept and conducted experiments to explore the validity of the approach. We show that our implementation of the LRAAM performs correctly under specific parameters. We also identify limitations in using LRAAM in this context.
  • Publication
    Métadonnées seulement
    Methodological Approach to Data-Centric Cloudific- ation of Scientific Iterative Workflows
    (: Springer, LNCS 10048, 2016-12-14)
    Kropf, Peter 
    The computational complexity and the constantly increas- ing amount of input data for scientific computing models is threatening their scalability. In addition, this is leading towards more data-intensive scientific computing, thus rising the need to combine techniques and in- frastructures from the HPC and big data worlds. This paper presents a methodological approach to cloudify generalist iterative scientific work- flows, with a focus on improving data locality and preserving perfor- mance. To evaluate this methodology, it was applied to an hydrologi- cal simulator, EnKF-HGS. The design was implemented using Apache Spark, and assessed in a local cluster and in Amazon Elastic Compute Cloud (EC2) against the original version to evaluate performance and scalability.
  • Publication
    Métadonnées seulement
    Lessons Learned from Applying Big Data Paradigms to a Large Scale Scientific Workflow
    (: CEUR-WS.org, 2016-11-14)
    Kropf, Peter 
    The increasing amount of data related to the execution of scientific workflows has raised awareness of their shift towards parallel data-intensive problems. In this paper, we deliver our experience with combining the traditional high-performance computing and grid-based approaches for scientific workflows, with Big Data analytics paradigms. Our goal was to assess and discuss the suitability of such data-intensive-oriented mechanisms for production-ready workflows, especially in terms of scalability, focusing on a key element in the Big Data ecosystem: the data-centric programming model. Hence, we reproduced the functionality of a MPI-based iterative workflow from the hydrology domain, EnKF-HGS, using the Spark data analysis framework. We conducted experiments on a local cluster, and we relied on our results to discuss promising directions for further research.
  • Publication
    Métadonnées seulement
    Cloudification of a Legacy Hydrological Simulator using Apache Spark
    (2016-9-14)
    Kropf, Peter 
    ;
    Lapin, Andrei 
    ;
    Carretero, Jesus
    ;
    Caíno-Lores, Silvina
    The field of hydrology usually relies on complex multiphysics systems and data collected from geographically distributed sensors in order to obtain good quality predictions and analysis of how wa- ter moves through the environment. Nowadays, the computational resources needed to run such com- plex simulators, and the increasing size of datasets related to the models have arisen an interest to- wards distributed infrastructures like clouds. This paper presents the results of applying a cloudifica- tion methodology to a legacy hydrological simulator (HydroGeoSphere), wrapped with an ensemble Kal- man filter. This work describes how the methodology was applied, the particularities of its implementation and configuration for the Apache Spark iterative map- reduce platform, and the results of an evaluation in a commodity cluster against an MPI implementation of the simulator.
  • Publication
    Accès libre
    Wireless Mesh Networks and Cloud Computing for Real Time Environmental Simulations
    (: Springer, 2014-4-22)
    Kropf, Peter 
    ;
    Schiller, Eryk 
    ;
    Brunner, Philip 
    ;
    Schilling, Oliver 
    ;
    Hunkeler, Daniel 
    ;
    Lapin, Andrei 
    Predicting the influence of drinking water pumping on stream and groundwater levels is essential for sustainable water management. Given the highly dynamic nature of such systems any quantitative analysis must be based on robust and reliable modeling and simulation approaches. The paper presents a wireless mesh-network framework for environmental real time monitoring integrated with a cloud computing environment to execute the hydrogeological simulation model. The simulation results can then be used to sustainably control the pumping stations. The use case of the Emmental catchment and pumping location illustrates the feasibility and effectiveness of our approach even in harsh environmental conditions.
  • Publication
    Accès libre
    Real-time Environmental Monitoring for Cloud-based Hydrogeological Modeling with HydroGeoSphere
    (: IEEE Computer Society, 2014)
    Lapin, Andrei 
    ;
    Schiller, Eryk 
    ;
    Kropf, Peter 
    ;
    Schilling, Oliver 
    ;
    Brunner, Philip 
    ;
    Jamakovic-Kapic, A.
    ;
    Braun, T.
    ;
    Maffioletti, S.
    This paper describes an architecture for real-time environmental modeling. It consists of a wireless mesh network equipped with sensors and a cloud-based infrastructure to perform real-time environmental sim- ulations using a physics-based model combined with an Ensemble Kalman Filter. The purpose of the system is to optimize groundwater abstraction close to a river. These initial studies demonstrate that the cloud infrastructure can simultaneously compute a large number of simula- tions, thus allowing for the implementation of Ensemble Kalman Filters in real-time.
  • Publication
    Métadonnées seulement
    Network Performance of the JBoss Application Server
    (: IEEE, 2013-10-22)
    Benothman, Nabil
    ;
    Clere, Jean-Frederic
    ;
    Schiller, Eryk 
    ;
    Kropf, Peter 
    ;
    Maucherat, Remy
    JBoss Application Server (AS) uses java.io and the Apache Portable Runtime (APR) project to provide its HTTP connectors. Due to new features of upcoming specifications of the Java Enterprise Edition (Java EE), the existing connectors shall be replaced by modern non blocking Input/Outputs (I/Os). In this study, we review some modern I/O frameworks such as NIO.2 introduced by Java SE 7 and XNIO3 developed by JBoss. We compare their network performance by running a series of stress tests on client-server applications of limited functionality. As a result, we select NIO.2 as the most appropriate framework to specify and implement a new JBoss connector. Finally, we compare our newly implemented Java connector against the existing APR-based one by means of network performance measures.