2008
DOI: 10.1007/978-3-540-68642-2_4
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Decentralised QoS-Management in Service Oriented Architectures

Abstract: Abstract. Traditional hierarchical Service Level Management (SLM) frameworks fail to cope with the challenges imposed by the runtime dynamics of Service Oriented Architectures (SOA). This paper introduces a decentralised management approach that successfully uses emerging selfmanagement techniques to realise a flexible SLM system and presents an architecture that implements this approach. The architecture consists of a modular self-manager framework that provides the basis for component-level and workflow-leve… Show more

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Cited by 13 publications
(5 citation statements)
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“…The approach presented here is further developed to support a selfmanagement approach that uses the accumulated performance data (shown in Figure 1), see [18] for details.…”
Section: Discussionmentioning
confidence: 99%
“…The approach presented here is further developed to support a selfmanagement approach that uses the accumulated performance data (shown in Figure 1), see [18] for details.…”
Section: Discussionmentioning
confidence: 99%
“…The SCA business components are wrapped inside an SCA composite to include the monitoring and management components and which provides the required interfaces. This equivalency is depicted in Figure 7, focusing on the Monitoring component only for better readability (and is similar to the approach of [16], which does not, however, targets runtime reconfiguration of the management layer). …”
Section: Generalizationmentioning
confidence: 94%
“…The analysis of the identified QoS factors with a valued score is presented in figure 2 showing factors on a scale of 0 (low) to 9 (high) representing their importance (I). The selected scores are for generic SOA applications and they are based on the wider research in the literature, real life experience and the views of the stakeholders [11] [18]. Thus, specific SOA applications with different user requirements might lead to different scores.…”
Section: Analytical Hierarchical Processmentioning
confidence: 99%