6,557 research outputs found

    Towards critical event monitoring, detection and prediction for self-adaptive future Internet applications

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    The Future Internet (FI) will be composed of a multitude of diverse types of services that offer flexible, remote access to software features, content, computing resources, and middleware solutions through different cloud delivery models, such as IaaS, PaaS and SaaS. Ultimately, this means that loosely coupled Internet services will form a comprehensive base for developing value added applications in an agile way. Unlike traditional application development, which uses computing resources and software components under local administrative control, FI applications will thus strongly depend on third-party services. To maintain their quality of service, those applications therefore need to dynamically and autonomously adapt to an unprecedented level of changes that may occur during runtime. In this paper, we present our recent experiences on monitoring, detection, and prediction of critical events for both software services and multimedia applications. Based on these findings we introduce potential directions for future research on self-adaptive FI applications, bringing together those research directions

    Model Based Development of Quality-Aware Software Services

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    Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

    Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

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    As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin

    A Framework for Quality-Driven Delivery in Distributed Multimedia Systems

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    In this paper, we propose a framework for Quality-Driven Delivery (QDD) in distributed multimedia environments. Quality-driven delivery refers to the capacity of a system to deliver documents, or more generally objects, while considering the users expectations in terms of non-functional requirements. For this QDD framework, we propose a model-driven approach where we focus on QoS information modeling and transformation. QoS information models and meta-models are used during different QoS activities for mapping requirements to system constraints, for exchanging QoS information, for checking compatibility between QoS information and more generally for making QoS decisions. We also investigate which model transformation operators have to be implemented in order to support some QoS activities such as QoS mapping

    Reconfigurable mobile communications: compelling needs and technologies to support reconfigurable terminals

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    Resilient Critical Infrastructure Management using Service Oriented Architecture

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    Abstract—The SERSCIS project aims to support the use of interconnected systems of services in Critical Infrastructure (CI) applications. The problem of system interconnectedness is aptly demonstrated by ‘Airport Collaborative Decision Making’ (ACDM). Failure or underperformance of any of the interlinked ICT systems may compromise the ability of airports to plan their use of resources to sustain high levels of air traffic, or to provide accurate aircraft movement forecasts to the wider European air traffic management systems. The proposed solution is to introduce further SERSCIS ICT components to manage dependability and interdependency. These use semantic models of the critical infrastructure, including its ICT services, to identify faults and potential risks and to increase human awareness of them. Semantics allows information and services to be described in such a way that makes them understandable to computers. Thus when a failure (or a threat of failure) is detected, SERSCIS components can take action to manage the consequences, including changing the interdependency relationships between services. In some cases, the components will be able to take action autonomously — e.g. to manage ‘local’ issues such as the allocation of CPU time to maintain service performance, or the selection of services where there are redundant sources available. In other cases the components will alert human operators so they can take action instead. The goal of this paper is to describe a Service Oriented Architecture (SOA) that can be used to address the management of ICT components and interdependencies in critical infrastructure systems. Index Terms—resilience; QoS; SOA; critical infrastructure, SLA

    Toward a Formal Semantics for Autonomic Components

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    Autonomic management can improve the QoS provided by parallel/ distributed applications. Within the CoreGRID Component Model, the autonomic management is tailored to the automatic - monitoring-driven - alteration of the component assembly and, therefore, is defined as the effect of (distributed) management code. This work yields a semantics based on hypergraph rewriting suitable to model the dynamic evolution and non-functional aspects of Service Oriented Architectures and component-based autonomic applications. In this regard, our main goal is to provide a formal description of adaptation operations that are typically only informally specified. We contend that our approach makes easier to raise the level of abstraction of management code in autonomic and adaptive applications.Comment: 11 pages + cover pag

    Unified radio and network control across heterogeneous hardware platforms

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    Experimentation is an important step in the investigation of techniques for handling spectrum scarcity or the development of new waveforms in future wireless networks. However, it is impractical and not cost effective to construct custom platforms for each future network scenario to be investigated. This problem is addressed by defining Unified Programming Interfaces that allow common access to several platforms for experimentation-based prototyping, research, and development purposes. The design of these interfaces is driven by a diverse set of scenarios that capture the functionality relevant to future network implementations while trying to keep them as generic as possible. Herein, the definition of this set of scenarios is presented as well as the architecture for supporting experimentation-based wireless research over multiple hardware platforms. The proposed architecture for experimentation incorporates both local and global unified interfaces to control any aspect of a wireless system while being completely agnostic to the actual technology incorporated. Control is feasible from the low-level features of individual radios to the entire network stack, including hierarchical control combinations. A testbed to enable the use of the above architecture is utilized that uses a backbone network in order to be able to extract measurements and observe the overall behaviour of the system under test without imposing further communication overhead to the actual experiment. Based on the aforementioned architecture, a system is proposed that is able to support the advancement of intelligent techniques for future networks through experimentation while decoupling promising algorithms and techniques from the capabilities of a specific hardware platform
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