SLAs are an integral part of all modern service provisioning operations. They have been a topic of discussion, research and development for many years but still the norm is the use of rigid, complex and not easy to automate Service Level Agreements. In this paper we are presenting a service framework that is leveraging the OCCI specification in order to facilitate standardized SLA provisioning and violation detection. This SLA as a Service (SLAaaS) offering is provided as an open source framework to any Service Provider that wants to efficiently enhance his infrastructure with SLA support.

As the sector of SaaS is being evolved, the need of portability and effective orchestration of Cloud-enabled applications over virtualised infrastructures is more apparent. In this paper we present a proof of concept (PoC) project together with industry partners which deals with the management of portable Cloud applications. Experimentation with a multi-tier Cloud application use case gives insights into the capabilities of the TOSCA specification (version 1). To realize support for a Cloud environment based on OpenStack and Opscode Chef, an environment that allows the execution and management of TOSCA service topologies has been developed. For the evaluation of the implemented system, we orchestrate the un-/deployment of the multi-tier Cloud application use case and in the end we discuss the results and experiences of this exercise.

Virtualization is the foundation of modern, cloud-based applications. The existence of virtual machines (VM) that host the components of such applications enables their portability and scalability. VMs are used in cloud infrastructures, and with dynamic operational requirements there is a need to move VMs within and across different clouds. The successful migration of VMs from one cloud to another should not always be considered as given. The goal of this paper is to devise and implement methods and conduct functional tests towards evaluating interoperability in cloud environments. We suggest a methodology for assessing the interoperability across different systems and we conduct a survey with a series of hypervisors and operating systems.

In modern utility computing infrastructures, like grids and clouds, one of the significant actions of a service provider is to predict the resources needed by the services included in its platform in an automated fashion for service provisioning optimization. Furthermore, a variety of software toolkits exist that implement an extended set of algorithms applicable to workload forecasting. However, their automated use as services in the distributed computing paradigm includes a number of design and implementation challenges. In this paper, a decoupled framework is presented, for taking advantage of software like GNU Octave in the process of creating and using prediction models during the service life cycle of a SOI. A performance analysis of the framework is also conducted. In this context, a methodology for creating parametric or gearbox services with multiple modes of operations based on the execution conditions is portrayed and is applied to transform the aforementioned service framework to optimize service performance. A new estimation algorithm is introduced, that creates performance rules of applications as black boxes, through the creation and usage of genetically optimized artificial neural networks. Through this combination, the critical parameters of the networks are decided through an evolutionary iterative process.

The emergence of Cloud technologies ultimately affected the service computing ecosystem introducing new roles and relationships as well as new architectural and business models. Along with the increase of the capabilities and potentials of the service providers came the increase of the information being available and the need to manage it in an efficient way. To this end, in this paper we present a management service architecture as well as the information model that the solution is based on. The model has been designed to serve a storage service provided by a Cloud infrastructure but the approach is implemented in a flexible and modular fashion in order to support different Cloud situations.

In this paper, we address the problem of managing SLAs in cloud computing environments. The idea is to take advantage of the content terms that concern the objects and support more efficient capabilities, such as quicker search and retrieval of the objects. As a result, the operational cost is reduced and consequently this fact lessens the customer's charge.

The advancements in distributed computing have driven the emergence of service-based infrastructures that allow for on-demand provision of ICT assets. Taking into consideration the complexity of distributed environments, significant challenges exist in providing and managing the offered on-demand resources with the required level of Quality of Service (QoS), especially for real-time interactive multimedia applications. Common to these applications is the service-oriented approach being followed, thus applications consist of application service components that interact in order to provide the corresponding application functionality. In this paper we present an architectural design of a complete Workflow Management System (WfMS) for enacting application service components that have been deployed in a Virtualized Environment. The WfMS aims at synchronizing the application components, monitoring their execution and handling faults while adhering to the QoS requirements of the application.

A constantly increasing number of applications from various scientific sectors are finding their way towards adopting grid technologies in order to take advantage of their capabilities: the advent of grid environments made feasible the solution of computational intensive problems in a reliable and cost-effective way. In this paper we present a grid-based approach for aggregation of data that are obtained from various sources (e.g. cameras, sensors) and their analysis with the use of genetic algorithms. By also taking into consideration general historical data and patient-specific medical information, we present the realization of the proposed approach with an application scenario for personalized healthcare and medicine.