Software as a Service (SaaS) is increasingly being adopted as a provision model where applications are hosted in a Cloud computing environment. To offer a SaaS with flexible functions at a low cost, the concept of composite SaaS was introduced as a combination of Cloud and Web services. Operating in a dynamic and volatile environment like the Cloud, a composite SaaS has very variable Quality of Service (QoS) parameters. Consequently, monitoring and adapting composite SaaS are vital means to guarantee QoS parameters defined in the Service Level Agreement (SLA). In this context, this paper proposes three Fuzzy algorithms for self-adaptive SaaS to prevent SLA violations for composite SaaS. The proposed algorithms have the merit of confronting three important issues, namely: the dependence of QoS parameters (e.g. availability) on low level metrics (e.g. uptime, downtime); the selection of service adaptation strategies that can cover both the business and
Cloud, composite SaaS, adaptation, fuzzy system
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