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Dynamic QoS Management and Optimization in Service-Based Systems
Dynamic QoS Management and Optimization in Service-Based Systems   (Citations: 6)
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Service-based systems that are dynamically composed at runtime to provide complex, adaptive functionality are currently one of the main development paradigms in software engineering. However, the Quality of Service (QoS) delivered by these systems remains an important concern, and needs to be managed in an equally adaptive and predictable way. To address this need, we introduce a novel, tool-supported framework for the development of adaptive service-based systems called QoSMOS (QoS Management and Optimization of Service-based systems). QoSMOS can be used to develop service-based systems that achieve their QoS requirements through dynamically adapting to changes in the system state, environment, and workload. QoSMOS service-based systems translate high-level QoS requirements specified by their administrators into probabilistic temporal logic formulae, which are then formally and automatically analyzed to identify and enforce optimal system configurations. The QoSMOS self-adaptation mechanism can handle reliability and performance-related QoS requirements, and can be integrated into newly developed solutions or legacy systems. The effectiveness and scalability of the approach are validated using simulations and a set of experiments based on an implementation of an adaptive service-based system for remote medical assistance.
Journal: IEEE Transactions on Software Engineering - TSE , vol. 37, no. 3, pp. 387-409, 2011
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    • ...1 More recently, probabilistic model checking has been used to guide self-optimisation in autonomic IT systems during their execution stage [2, 3, 4]...
    • ...A technique for learning the state transition probabilities pij for the DTMC (1) when only a priori estimates p 0 ij, 1 i;j n, are available initially is presented in [5], and successfully used in the context of workow QoS management in [2]...
    • ...system will transition from state si to precisely one state from S. The work presented in [2] uses theoretical results from [13] and the Bayes’ rule to derive the updating rule for estimating the probability pij after the observation of the k-th transition from state si to another state in S as...
    • ...The updating rule (4) was shown [2, 5] to be eective in scenarios where the actual probability pij diers from the a Figure 3: The ageing function age is used to weigh...
    • ...As a further step in exploiting the new technique, we are considering integrating it into the QoS management and optimisations framework from [2]...

    Radu Calinescuet al. Using observation ageing to improve markovian model learning in QoS en...

    • ...Research done in QoS management is vast and frequently accounts for various aspects, namely charges for service, commitment to provide a specified level of service, and penalties [8], [21]...

    Sergio Pacheco-Sanchezet al. Markovian Workload Characterization for QoS Prediction in the Cloud

    • ...In addition, we are also interested in speeding up our approaches via incremental verification and analysis, and developing online techniques to provide support for on-the-fly Connector synthesis [5], such as those based on [7]...

    Felicita Di Giandomenicoet al. Dependability Analysis and Verification for Connected Systems

    • ...While quantitative verification is traditionally used for the off-line analysis of system models such as Markov chains and Markov decision processes, recent research has successfully employed an on-line version of the technique to support self-optimisation in adaptive computer systems [13,14,15]...
    • ...– Dynamic QoS management in service-based systems [15]...
    • ...For instance, the study carried out in [15] found that over 70% of the bioinformatics workflows from the widely used myExperiment workflow repository 2 comprise between one and eight web service invocations...
    • ...The options explored in the effort to address this challenge include a combination of software engineering techniques and novel quantitative verification algorithms [14,15]...
    • ...Figure 1) has been successful [20,15,21], there are multiple applications in which systems undergo unpredictable changes that require structural model changes (e.g., to reflect components leaving or joining the system dynamically)...

    Radu Calinescuet al. Formal Methods @ Runtime

    • ...These include: probabilistic counterexample generation [4,3], verification under fairness [8] and under restricted classes of adversaries [47,29], parametric model checking [51], synthesis of parameters [52] and models [28], and run-time probabilistic model checking [24,44]...

    Vojtěch Forejtet al. Automated Verification Techniques for Probabilistic Systems

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