Approach overview Sample Clauses

Approach overview. In order to overcome the problems that have been enumerated in the intro- duction P.1, P.2, P.3, P.4, P.5, P.6 and P.7, we propose an approach that consists in developing an SPL, named SPLSP , for the feature modeling and the mass-customization of SPs. In Fig. 2, we introduce an overview of our approach including its implementation steps that will be presented in the following.
Sample 1
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Approach overview. In this Section, we provide an overview on the QualiMaster adaptation approach and, thus, detail the initial overview given in Section 3. We structure this section along the MAPE-K cycle (monitor- analyze-plan-execute over a common knowledge base) [22, 76, 90] and discuss how the individual parts of the cycle will be realized in QualiMaster. An overview is depicted in Figure 15. As indicated in Section 3, an important part of the knowledge base is the runtime configuration. It consists of the configuration used for the instantiation of the QualiMaster infrastructure and the runtime variables indicating the actual state of the system. Examples for runtime variables are selected algorithms, parameter settings and observables such as quality parameters. In particular, configuration values used during the instantiation of the QualiMaster infrastructure will be available, but, unless marked by specific IVML attributes, considered as constant during runtime. In contrast, runtime variables change during runtime (in particular quality parameters as observed by monitoring) or are being changed by the adaptation such as the currently selected algorithms. Sensor / Monitor Effector / Adaptation Event Policy (IVML) Analyze Adaptation Layer Plan Knowledge Monitor Execute / Enact Sensor / Monitor Effector / Enaction Command A prerequisite to adaptation is that the system being adapted is monitored. Basically, the quality parameters are defined in the Configuration Meta Model (see Section 7.2.2). All quality parameters that are either used in the (SLA) constraints of the Configuration Meta Model or in the specification Coordination / Execution Layer Figure 15: MAPE-K adaptation cycle in QualiMaster (based on [76]) of the adaptive behavior (see Section 8.2) are considered for monitoring (through the platform instantiation). While the values of the quality parameters are physically monitored in the Execution Layer (through instrumented code, generated code or existing interfaces as described in D5.1), the Monitoring Layer of the QualiMaster infrastructure receives, aggregates and, if required, persists the values in terms of quality profiles in the Data Management Layer. Next, the actual values of the quality parameters are analyzed. In the architectural blueprint of adaptive systems [76] as well as in many approaches in literature, this is done by an own component. However, in QualiMaster, the Monitoring Layer mainly acts as an aggregator and overall control mechanism for ...
Sample 1

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