Andreas Dittrich

Tag: Service dependability

  • Service Availability and Discovery Responsiveness – A User-Perceived View on Service Dependability

    Service Availability and Discovery Responsiveness – A User-Perceived View on Service Dependability Author:
    Andreas Dittrich

    Ph.D. Thesis, submitted to the Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin, December 9, 2014. Oral defense March 20, 2015.
    Grade: magna cum laudae.

    Reviewers:
    Prof. Dr. Miroslaw Malek, Lugano, Switzerland
    Prof. Dr. Alexander Reinefeld, Berlin, Germany
    Prof. Dr. Jörg Kaiser, Magdeburg, Germany

    Download: published version, meta information

    Dependability of service provision is one of the primary goals in modern networks. Since providers and clients are part of a connecting Information and Communications Technology (ICT) infrastructure, service dependability varies with the position of actors as the ICT devices needed for service provision change. We present two approaches to quantify user-perceived service dependability. The first is a model-driven approach to calculate instantaneous service availability. Using input models of the service, the infrastructure and a mapping between the two to describe actors of service communication, availability models are automatically created by a series of model to model transformations. The feasibility of the approach is demonstrated using exemplary services in the network of University of Lugano, Switzerland. The second approach aims at the responsiveness of the service discovery layer, the probability to find service instances within a deadline even in the presence of faults, and is the main part of this thesis. We present a hierarchy of stochastic models to calculate user-perceived responsiveness based on monitoring data from the routing layer. Extensive series of experiments have been run on the Distributed Embedded Systems (DES) wireless testbed at Freie Universität Berlin. They serve both to demonstrate the shortcomings of current discovery protocols in modern dynamic networks and to validate the presented stochastic models. Both approaches demonstrate that the dependability of service provision indeed differs considerably depending on the position of service clients and providers, even in highly reliable wired networks. The two approaches enable optimization of service networks with respect to known or predicted usage patterns. Furthermore, they anticipate novel service dependability models which combine service discovery, timeliness, placement and usage, areas that until now have been treated to a large extent separately.

  • Responsiveness of Service Discovery in Wireless Mesh Networks

    Responsiveness of Service Discovery in Wireless Mesh Networks Authors:
    Andreas Dittrich
    Daniel Solis Herrera
    Pablo Coto
    Miroslaw Malek

    20th IEEE Pacific Rim International Symposium on Dependable Computing, PRDC 2014, Singapore, November 18-21, 2014

    Download: accepted version, final published version

    Service Discovery (SD) is an integral part of service networks. Before a service can be used, it needs to be discovered successfully. Thus, a comprehensive service dependability analysis needs to consider the dependability of the SD process. As a time-critical operation, an important property of SD is responsiveness: the probability of successful discovery within a deadline, even in the presence of faults. This is especially true for dynamic networks with complex fault behavior such as wireless networks. We present results of a comprehensive responsiveness evaluation of decentralized SD, specifically active SD using the Zeroconf protocol. The ExCovery experiment framework has been employed in the Distributed Embedded System (DES) wireless testbed at Freie Universität Berlin. We present and discuss the experiment results and show how SD responsiveness is affected by the position and number of requesters and providers as well as the load in the network. Results clearly demonstrate that in all but the most favorable conditions, the configurations of current SD protocols struggle to achieve a high responsiveness. We further discuss results reflecting the long-term behavior of the testbed and how its varying reliability impacts SD responsiveness.

  • Model-Driven Evaluation of User-Perceived Service Availability

    Model-Driven Evaluation of User-Perceived Service Availability Authors:
    Andreas Dittrich
    Rafael Rezende

    14th European Workshop on Dependable Computing (EWDC), Coimbra, Portugal, May 15-16, 2013

    Download: accepted version, the final publication is available at link.springer.com

    Service-oriented architecture (SOA) has emerged as an approach to master growing system complexity by proposing services as basic building elements of system design. However, it remains difficult to evaluate dependability of such distributed and heterogeneous functionality as it depends highly on the properties of the enabling information and communications technology (ICT) infrastructure. Moreover, every specific pair service client and provider can utilize different ICT components, constituting for the user-perceived view of a service. We provide a model-driven methodology to automatically create reliability block diagrams of such views. Given a service description, a network topology model and a pair service client and provider, it identifies relevant ICT components and generates a user-perceived service availability model (UPSAM). We then use this UPSAM to calculate the steady-state availability of different views on an exemplary mail service deployed in the network infrastructure of University of Lugano, Switzerland.

  • A Model for Evaluation of User-Perceived Service Properties

    A Model for the Evaluation of User-Perceived Service Properties Authors:
    Andreas Dittrich
    Igor Kaitovic
    Cristina Murillo
    Rafael Rezende

    27th IEEE International Symposium on Parallel Distributed Processing, Workshops and PhD Forum, IPDPSW 2013, Boston, MA, USA, May 20-24, 2013

    Download: accepted version, final published version

    An ever-increasing number of both functional and non-functional requirements has resulted in growing system complexity which demands new solutions in system modeling and evaluation. As a remedy, service-oriented architecture (SOA) offers services as basic building elements of system design. Service dependability is highly dependent on the properties of the underlying information and communications technology (ICT) infrastructure. This is especially true for the user-perceived dependability of a specific pair service client and provider as every pair may utilize different ICT components. We provide a model for the description of ICT components and their non-functional properties based on the Unified Modeling Language (UML). Given a service description, a network topology model and a pair service client and provider, we propose a methodology to automatically identify relevant ICT components and generate a user-perceived service infrastructure model (UPSIM). We demonstrate the feasibility of the methodology by applying it to parts of the service network infrastructure at University of Lugano (USI), Switzerland. We then show how this methodology can be used to facilitate user-perceived service dependability analysis.

  • Self-Aware Adaptive Service Networks with Dependability Guarantees

    Self-Aware Adaptive Service Networks with Dependability Guarantees Author:
    Andreas Dittrich

    Proceedings of the Joint Workshop of the German Research Training Groups in Computer Science, Algorithmic synthesis of reactive and discrete-continuous systems (AlgoSyn), Dagstuhl, Germany, May 31 – June 2, 2010

    Download: extended abstract

    Disasters striking in inhabited areas pose a significant risk to the development and growth of modern societies. The impact of any disaster would be severe. In case a disaster strikes, fast and safe mitigation of damages is important. Information and communication technology (ICT) plays a crucial role in helping reconnaissance and first response teams on disaster sites.

    Most rescue teams bring their own network equipment to use several IT services. Many of these services (e.g., infrastructure, location, communication) could be shared among teams but most of the time they are not. Coordination of teams is partly done by pen and paper-based methods. A single network for all participating teams with the possibility to reliably publish, discover and use services would be of great benefit.

    Despite the participating teams and course of action being different on every site, described service networks display certain common properties: They arise spontaneously,
    the number of nodes and their capabilities are subject to high fluctuation, the number and types of services are also fluctuating strongly and there is no global administrative configuration.

    Because of these properties all network layers involved would need to be configured automatically. Based on the Internet Protocol (IP) — the only well-established global networking standard — a number of mechanisms promise to automatically configure service networks. In disaster management scenarios, where various services are critical for operation, mission control could benefit from these mechanisms by getting a live view of all active services and their states. It needs to be investigated if and how they are applicable.

    Given an ad-hoc, auto-configuring service network, how and to what extent can we guarantee dependability properties such as availability, the ability to perform in the presence of faults (performability) and ultimately the ability to sustain certain levels of availability or performability (survivability) for critical services at run-time?

    The goal of this dissertation is to provide a comprehensive dependability evaluation for such heterogenous and dynamic service networks. A run-time dependability cycle is being embedded into the network. In this cycle, the network is constantly monitored.
    A distributed service discovery layer provides network-wide service presence monitoring. This will be extended to provide monitoring for availability and performability assessment. Based on monitoring data, dependability properties are evaluated at run-time. The survivability of critical services can be estimated by calculating the expected availability or performability with a given fault model. If necessary, adaptation measures are triggered which in turn can cause the monitoring to be reconfigured. Even if no adaptation is possible, run-time awareness of critical states is already a huge benefit. This cycle is the base of a self-aware adaptive service network.