This article describes how currently, service level agreements (SLAs) assurance forms one of the major challenges for cloud computing (CC) in order to guarantee quality of service (QoS) in real-time and control SLA violations. However, due to the highly dynamic nature of this open environment, it is important to have a binding agreement between all the service parties for ensuring trust while fulfilling the expected QoS. To properly operate and manage such complex situations, an effective and efficient monitoring is crucial. The participation of a trusted third party (TTP) is necessary in order to resolve conflicts between involved parties. This article proposes an autonomic SLA monitoring framework managed by TTP composed of two modules: the first one SLA establishment module, which aims at providing support for automated SLA generation and management. The second one, a service monitoring module to dynamically monitor QoS metrics by detecting SLA violations at runtime to verify compliances for the respective SLAs, and to propose a mechanism for an adaptive remedy rectification, as a contribution at the third maturity level of the autonomic computing paradigm as defined by IBM. The framework is validated with scenarios on response time and availability, the results obtained are promising. They confirm that this framework manages SLAs in an efficient way as it detects all violations to be communicated to concerned parties, and identifies particular penalty clauses that can be used to modify the reputation of a provider over time. The TTP framework equipped with such reputation module can provide real-time assessment for consumers informed decision making to continue using a service or to migrate to another service provider in the case of service degradation. This creates a fair competitiveness between providers and hence improves service performance and the reliability in the cloud.

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Abstract:In open dynamic multi-agent systems, trust is commonly considered as a critical concept to be handled and managed. Computational trust models are a kinds of formal models that have been proposed to manage trust in such situation. These models present a new form of distributed intelligence in virtual societies and collective intelligence. However, the diversity of those models makes user confused about which one to choose. Different testbeds have been established to evaluate trust and reputation models and verify their robustness and efficiency. However, a lack of flexibility to handle scenarios related to multi-context trust models arise with those testbeds. We present in this paper a framework for evaluating computational trust models that provides to users more flexibility while comparing trust models in open systems and shows analysis results in chart diagrams. The ultimate objective is to evaluate and classify available computational trust models.

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