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Kishor S. Trivedi - One of the best experts on this subject based on the ideXlab platform.

  • LADC - Parametric Uncertainty Propagation through Dependability Models
    2018 Eighth Latin-American Symposium on Dependable Computing (LADC), 2018
    Co-Authors: Hiroyuki Okamura, Tadashi Dohi, Kishor S. Trivedi
    Abstract:

    The uncertainty propagation is to investigate the effect of errors in Model input parameters on the system output measure in probability Models. In this paper, we present a moment-based approach of the uncertainty propagation of Model input parameters. The presented approach requires only the fist two moments of Model parameters, and has an advantage in terms of computation over the closed-form, numerical and sampling-based approaches for uncertainty propagation. The paper presents the properties of moment-based approach by comparing the existing Bayes estimation for the uncertainty propagation in a simple reliability Model. An Availability Model of a server with virtual machines is used to illustrate the applicability of our method in practical problems.

  • Modeling and analysis of software rejuvenation in a server virtualized system with live vm migration
    Performance Evaluation, 2013
    Co-Authors: Fumio Machida, Dong Seong Kim, Kishor S. Trivedi
    Abstract:

    As server virtualization is used in a number of IT systems, the unAvailability of virtual machines (VM) on server virtualized systems becomes a significant concern. Software rejuvenation is a promising technique for improving the Availability of server virtualized systems as it can postpone or prevent failures caused by software aging in both the VM and the underlying virtual machine monitor (VMM). In this paper, we study the effectiveness of a combination of VMM rejuvenation and live VM migration. When a VMM needs to be rejuvenated, the hosted VMs running on the VMM can be moved to another host using live VM migration and continue the execution even during the VMM rejuvenation. We call this technique Migrate-VM rejuvenation and construct an Availability Model in the stochastic reward net for evaluating it in comparison with the conventional approaches; Cold-VM rejuvenation and Warm-VM rejuvenation. The designed Model enables us to find the optimum combinations of rejuvenation trigger intervals that maximize the Availability of VM. In terms of the maximum VM Availability, Migrate-VM rejuvenation is potentially the best approach. However, the advantage of Migrate-VM rejuvenation depends on the type of live VM migration (stop-and-copy or pre-copy) and the policy for migration back to the original host after VMM rejuvenation (return-back or stay-on). Through numerical examples, we show that ''pre-copy'' live VM migration is encouraged rather than pure ''stop-and-copy'' migration and it is better to return back VM to the original host soon after the VMM rejuvenation (i.e., ''return-back'' rather than ''stay-on'' policy) for high-Availability. The effect of the VMM rejuvenation technique on the expected number of transactions lost is also studied by combining the Availability Model with an M/M/1/n queueing Model.

  • a scalable Availability Model for infrastructure as a service cloud
    Dependable Systems and Networks, 2011
    Co-Authors: Francesco Longo, Rahul Ghosh, Vijay K Naik, Kishor S. Trivedi
    Abstract:

    High Availability is one of the key characteristics of Infrastructure-as-a-Service (IaaS) cloud. In this paper, we show a scalable method for Availability analysis of large scale IaaS cloud using analytic Models. To reduce the complexity of analysis and the solution time, we use an interacting Markov chain based approach. The construction and the solution of the Markov chains is facilitated by the use of a high-level Petri net based paradigm known as stochastic reward net (SRN). Overall solution is composed by iteration over individual SRN sub-Model solutions. Dependencies among the sub-Models are resolved using fixed-point iteration, for which existence of a solution is proved. We compare the solution obtained from the interacting sub-Models with a monolithic Model and show that errors introduced by decomposition are insignificant. Additionally, we provide closed form solutions of the sub-Models and show that our approach can handle very large size IaaS clouds.

  • SRDS - Candy: Component-based Availability Modeling Framework for Cloud Service Management Using SysML
    2011 IEEE 30th International Symposium on Reliable Distributed Systems, 2011
    Co-Authors: Fumio Machida, Ermeson Andrade, Dong Seong Kim, Kishor S. Trivedi
    Abstract:

    High-Availability assurance of cloud service is a critical and challenging issue for cloud service providers. To quantify the Availability of cloud services from both architectural and operational points of views, Availability Modeling and evaluation are essential. This paper presents a component-based Availability Modeling framework, named Candy, which constructs a comprehensive Availability Model semi-automatically from system specifications described by Systems Modeling Language (SysML). SysML diagrams are translated into components of Availability Model and the components are assembled together to form the entire Availability Model in Stochastic Reward Nets (SRNs). In order to incorporate the maintenance operations of cloud services in Availability Models, Candy defines the translation rules from Activity diagram to SRN and synchronizes the related SRNs according to SysML allocation notations. The feasibility of the proposed Modeling and Availability evaluation process is studied by an illustrative example of a web application service hosted on a cloud infrastructure having multiple failure isolation zones and automatic scale-up function.

  • SRDS - Uncertainty Propagation in Analytic Availability Models
    2010 29th IEEE Symposium on Reliable Distributed Systems, 2010
    Co-Authors: Amita Devaraj, Kesari Mishra, Kishor S. Trivedi
    Abstract:

    In this paper, we discuss a Monte Carlo sampling based method for propagating the epistemic uncertainty in Model parameters, through the system Availability Model. We also outline methods to compute the number of samples needed to obtain a desired confidence interval for various scenarios. We illustrate this method with a real system example and discuss the results obtained. While our example discusses confidence interval for system Availability, this method can be directly applied to compute uncertainty for other dependability, performance and perform ability measures, computed by solving stochastic analytic Models. We also emphasize the fact that no simulation is carried out in our method but a repeated sampling is performed over the parameter space followed by the execution of the analytic Model with the final phase being the statistical analysis of the output vector.

Shigeru Yamada - One of the best experts on this subject based on the ideXlab platform.

  • ISAS - User-perceived software service Availability Modeling with reliability growth
    Service Availability, 2008
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    Most of conventional software Availability Models often assume only up and down state for the time-dependent behavior of a software-intensive system. In this paper, we develop a plausible software service Availability Model considering the degradation of system service performance and the software reliability growth process in operation. We assume that the software system has two operational states from the viewpoint of the end user: one is providing with service performance according to specification and the other is with degraded service performance. The time-dependent behavior of the system alternating between up and down state is described by a Markov process. This Model can derive instantaneous software service Availability defined as the expected value of possible service processing quantity per unit time at a specified time point. Finally, we show several numerical examples of the measures to analyze the relationship between the service Availability evaluation and software reliability growth characteristic.

  • A Markovian software Availability Model with a geometrically decreasing perfect debugging rate
    International Journal of Manufacturing Technology and Management, 2003
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    This paper discusses a software Availability Model considering an imperfect debugging environment where the detected faults are not always corrected and removed from the software system. In particular, we assume that perfect debugging activities become more difficult with the increasing number of corrected faults. The failure and restoration characteristics of the system are related to the cumulative number of corrected faults. The time-dependent behaviour of the system alternating between up and down states is described by a Markov process. From this Model, we can derive several stochastic quantities for software Availability measurement.

  • Markovian Availability Modeling for software‐intensive systems
    International Journal of Quality & Reliability Management, 2000
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    It is important to take into account the trade‐off between hardware and software systems when total computer‐system reliability/performance is evaluated and assessed. Develops an Availability Model for a hardware‐software system. The system treated here consists of one hardware and one software subsystem. For the software subsystem, in particular, it is supposed that: the restoration actions are not always performed perfectly; the restoration times for later software failures become longer; and reliability growth occurs in the perfect restoration action. The hardware‐ and software‐failure occurrence phenomena are described by a constant and a geometrically decreasing hazard rate, respectively. The time‐dependent behavior of the system is described by a Markov process. Useful expressions for several quantitative measures of system performance are derived from this Model. Finally, numerical examples are presented for illustration of system Availability measurement and assessment.

  • MARKOVIAN Availability MEASUREMENT WITH TWO TYPES OF SOFTWARE FAILURES DURING THE OPERATION PHASE
    International Journal of Reliability Quality and Safety Engineering, 1999
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    This paper develops a plausible software Availability Model considering two types of failures during the operation phase. The first type is caused by the faults that could not be detected/corrected during the testing phase and the second type caused by those introduced by deviating from the specification during the operation phase. The former and the latter types of software failure-occurrence phenomena are described by a geometrically decreasing and a constant hazard rate, respectively. This Model also describes the imperfect debugging environment in which a debugging activity does not always remove a fault perfectly. Taking notice of the cumulative number of faults corrected during the operation phase, we use a Markov process to describe the time-dependent behavior of the software system. Several quantitative measures of software system performance are derived from this Model. Finally, numerical examples are presented for illustration of software Availability measurement.

Fabio Vitale - One of the best experts on this subject based on the ideXlab platform.

  • pam sad ubiquitous car parking Availability Model based on v2v and smartphone activity detection
    International Conference on Intelligent Interactive Multimedia Systems and Services, 2018
    Co-Authors: Walter Balzano, Fabio Vitale
    Abstract:

    GNSS based systems (like GPS or GLONASS) for outdoor localization are nowadays widespread in common smartphones. Vehicle-2-vehicle technology allows vehicles to communicate via wireless to share any kind of information and detect mutual distances via RSS-to-distance evaluation. Smartphones can be used to detect when an user switches between car driving, walking and several other kind of activities.

  • PAM-SAD: Ubiquitous Car Parking Availability Model Based on V2V and Smartphone Activity Detection
    Intelligent Interactive Multimedia Systems and Services 2017, 2018
    Co-Authors: Walter Balzano, Fabio Vitale
    Abstract:

    GNSS based systems (like GPS or GLONASS) for outdoor localization are nowadays widespread in common smartphones. Vehicle-2-vehicle technology allows vehicles to communicate via wireless to share any kind of information and detect mutual distances via RSS-to-distance evaluation. Smartphones can be used to detect when an user switches between car driving, walking and several other kind of activities.In this paper we discuss a novel methodology to discover nearest available street-parking spot using a smart combination of V2V, GNSS systems and smartphone-driven activity detection. In order to achieve system ubiquitousness across large areas (beyond the size of a single city), while still keeping low computation requirements, for localization purposes we only consider a fragment of the whole network of parked cars. Additionally we consider recognition of newly available parking clusters (for instance, in case of a fair or other kind of events) and disqualification of previously available spots (in case of work in progress or permanent street modifications). Smartphone activity detection is therefore used in tandem with V2V to mark new parking Availability or occupancy based on user driving or walking away or toward the vehicle. When the user stops the car and starts walking, the vehicle is informed by the user smartphone of the context switch, and shares this positional information with nearby cars; when the user then goes back to his car and starts driving, the vehicle informs the local network of the newly available spot.

Kamel Barkaoui - One of the best experts on this subject based on the ideXlab platform.

  • Network Availability Modeling of VMIMO link in Multi-hop Wireless Network
    2012
    Co-Authors: Mohamed Escheikh, Kamel Barkaoui
    Abstract:

    Cooperative diversity or virtual antenna arrays enables transmission range extension and provides performance enhancements in wireless Multi-hop relay networks, when compared with relaying non cooperative diversity based schemes. Moreover Cooperative diversity allows better reliability to link failure and lead to a more efficient transmission that is of particular interest in mobile environment. In this paper we present a quantitative approach to analyze the steady state Availability analysis of a virtual antenna array link (VMIMO) subject to failures in a multi-hop wireless network using cooperative diversity and assuming Markovian properties. We propose an end to end VMIMO Availability Model enabling to express performance measure such as failure frequency and failure rate. These measures quantify failure impact on VMIMO link Availability.

  • ISCC - Network Availability Modeling of VMIMO link in multi-hop wireless network
    2012 IEEE Symposium on Computers and Communications (ISCC), 2012
    Co-Authors: Mohamed Escheikh, Kamel Barkaoui
    Abstract:

    Cooperative diversity or virtual antenna arrays enables transmission range extension and provides performance enhancements in wireless Multi-hop relay networks, when compared with relaying non cooperative diversity based schemes. Moreover Cooperative diversity allows better reliability to link failure and lead to a more efficient transmission that is of particular interest in mobile environment. In this paper we present a quantitative approach to analyze the steady state Availability analysis of a virtual antenna array link (VMIMO) subject to failures in a multi-hop wireless network using cooperative diversity and assuming Markovian properties. We propose an end to end VMIMO Availability Model enabling to express performance measure such as failure frequency and failure rate. These measures quantify failure impact on VMIMO link Availability. Our Model generalizes Availability Model given in [1] and may be exploited using the same approach presented in [1] to deduce survivability performance measures such that excess loss due to failure (ELF) and excess delay due to failure (EDF).

Koichi Tokuno - One of the best experts on this subject based on the ideXlab platform.

  • ISAS - User-perceived software service Availability Modeling with reliability growth
    Service Availability, 2008
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    Most of conventional software Availability Models often assume only up and down state for the time-dependent behavior of a software-intensive system. In this paper, we develop a plausible software service Availability Model considering the degradation of system service performance and the software reliability growth process in operation. We assume that the software system has two operational states from the viewpoint of the end user: one is providing with service performance according to specification and the other is with degraded service performance. The time-dependent behavior of the system alternating between up and down state is described by a Markov process. This Model can derive instantaneous software service Availability defined as the expected value of possible service processing quantity per unit time at a specified time point. Finally, we show several numerical examples of the measures to analyze the relationship between the service Availability evaluation and software reliability growth characteristic.

  • A Markovian software Availability Model with a geometrically decreasing perfect debugging rate
    International Journal of Manufacturing Technology and Management, 2003
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    This paper discusses a software Availability Model considering an imperfect debugging environment where the detected faults are not always corrected and removed from the software system. In particular, we assume that perfect debugging activities become more difficult with the increasing number of corrected faults. The failure and restoration characteristics of the system are related to the cumulative number of corrected faults. The time-dependent behaviour of the system alternating between up and down states is described by a Markov process. From this Model, we can derive several stochastic quantities for software Availability measurement.

  • Markovian Availability Modeling for software‐intensive systems
    International Journal of Quality & Reliability Management, 2000
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    It is important to take into account the trade‐off between hardware and software systems when total computer‐system reliability/performance is evaluated and assessed. Develops an Availability Model for a hardware‐software system. The system treated here consists of one hardware and one software subsystem. For the software subsystem, in particular, it is supposed that: the restoration actions are not always performed perfectly; the restoration times for later software failures become longer; and reliability growth occurs in the perfect restoration action. The hardware‐ and software‐failure occurrence phenomena are described by a constant and a geometrically decreasing hazard rate, respectively. The time‐dependent behavior of the system is described by a Markov process. Useful expressions for several quantitative measures of system performance are derived from this Model. Finally, numerical examples are presented for illustration of system Availability measurement and assessment.

  • MARKOVIAN Availability MEASUREMENT WITH TWO TYPES OF SOFTWARE FAILURES DURING THE OPERATION PHASE
    International Journal of Reliability Quality and Safety Engineering, 1999
    Co-Authors: Koichi Tokuno, Shigeru Yamada
    Abstract:

    This paper develops a plausible software Availability Model considering two types of failures during the operation phase. The first type is caused by the faults that could not be detected/corrected during the testing phase and the second type caused by those introduced by deviating from the specification during the operation phase. The former and the latter types of software failure-occurrence phenomena are described by a geometrically decreasing and a constant hazard rate, respectively. This Model also describes the imperfect debugging environment in which a debugging activity does not always remove a fault perfectly. Taking notice of the cumulative number of faults corrected during the operation phase, we use a Markov process to describe the time-dependent behavior of the software system. Several quantitative measures of software system performance are derived from this Model. Finally, numerical examples are presented for illustration of software Availability measurement.