Infrastructure as a service (IaaS) systems offer on demand virtual infrastructures so reliably and flexibly that users expect a high service level. Therefore, even with regards to internal IaaS behaviour, production clouds only adopt novel ideas that are proven not to hinder established service levels. To analyse their expected behaviour, new ideas are often evaluated with simulators in product...

Current cloud platforms are based on two mainstream models: Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). Both approaches entail strengths and weaknesses that we collect and present in this paper and we conclude the need to devise a new approach, based on graphical models, to overcome the imposed limitations. This model driven approach is introduced and slightly described...

I. Introduction In cloud computing, the cloud service providers (CSPs), such as Amazon, are able to deliver various services to cloud users with the help of powerful datacenters [1]. Cloud can provide a pool of resources to many user and organization without investment of infrastructure. Cloud computing also includes online applications, such as those offered through the configurable resources ...

With the increase of centralization of resources in IT-infrastructure and the growing amount of cloud services, database management systems (DBMS) will be more and more outsourced to Infrastructure-as-a-Service (IaaS) providers. The outsourcing of entire databases, or the computation power for processing Big Data to an external provider also means that the provider has full access to the inform...

This paper proposes an architecture for optimized resource allocation in Infrastructure-as-a-Service (IaaS)-based cloud systems. Current IaaS systems are usually unaware of the hosted application’s requirements and therefore allocate resources independently of its needs, which can significantly impact performance for distributed data-intensive applications. To address this resource allocation p...