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 production IaaS system-like scenarios. For instance, new research could enable collaboration amongst several layers of schedulers or could consider new optimisation objectives such as energy consumption. Unfortunately, current cloud simulators are hard to employ and they often have performance issues when several layers of schedulers interact in them. To target these issues, a new IaaS simulation framework (called DISSECT-CF) was designed. The new simulator's foundation has the following goals: easy extensibility, support energy evaluation of IaaSs and to enable fast evaluation of many scheduling and IaaS internal behaviour related scenarios. In response to the requirements of such scenarios, the new simulator introduces concepts such as: a unified model for resource sharing and a new energy metering framework with hierarchical and indirect metering options. Then, the comparison of several simulated situations to real-life IaaS behaviour is used to validate the simulator's functionality. Finally, a performance comparison is presented between DISSECT-CF and some currently available simulators.Comment: 28 pages, 17 figures, preprint version of the paper accepted by Simulation Modelling Practice and Theor

With the rise of internet of things (IoT) technology, it is anticipated that large-scale sensor-based systems will permeate society, calling for novel methodologies to design, test, and operate these systems. IoT relies on networked interconnected physical devices often featuring computational capabilities. The sheer number of these interconnected devices plays a key role in the IoT revolution. For example, Gartner research predicts that IoT will connect up to 50 to 100 billion devices by 2020. It is estimated that IoT will generate ~1.7 trillion US dollars in value by 2020 with an approximate growth rate of 20% year over year.

Cloud computing has enabled elastic and on-demand service provisioning to achieve more efficient resource utilisation and quicker responses to varying application loads. Virtual machines, the building blocks of clouds, can be created using provider specific templates stored in proprietary repositories, which may lead to provider lock-in and decreased portability. Despite these enabling technologies, large scale service oriented applications are still mostly inelastic. Such applications often use monolithic services that limit the elasticity (e.g., by obstructing the replicability of parts of a monolithic service). Decomposing these services (leading to smaller, more targeted and more modular services) would open towards elasticity, but the decomposition process is mostly manual. This paper introduces a methodology for decomposing monolithic services to several so called microservices. The proposed methodology applies several outcomes of the ENTICE project (namely its image synthesis and optimisation tools). Finally, the paper provides insights on how these outcomes help revitalise past monolithic services, and what techniques are applied to aid future microservice developers.

Cloud computing is a newly emerged research infrastructure that builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. In this paper we present an architecture for SLA-based resource virtualization that provides an extensive solution for executing user applications in Clouds. This work represents the first attempt to combine SLA-based resource negotiations with virtualized resources in terms of on-demand service provision resulting in a holistic virtualization approach. The architecture description focuses on three topics: agreement negotiation, service brokering and deployment using virtualization. The contribution is also demonstrated with a real-world case study.