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Providing realistic production environment for deployment of complex students' projects can be quite a challenge for the university computing centers. While alternatives such as using public/private clouds exist, enabling the students to focus on core project deployment instead of system administration of a production environment in general requires an alternative approach. The proposed platform as a service solution relates to the three most important requirements of such a system: scalability, ease of use, user isolation and security.

When moving cloud computing towards the edge in order to provide low latency and location-based Internet services, there are additional considerations that need to be introduced in the traditional cloud approaches to adapt them to fog computing. This paper discusses a proposal for resource allocation and migration strategies adapted specifically to fog computing. The proposal is based on the concept of virtual and physical communities and it has already shown its efficiency when applied to cloud computing. Simulation-based scenarios provide the performance of our community-based proposal following the geographical trajectory of mobile users.

New Grid and cloud solutions for distributed data mining and data processing are needed for execution of data intensive workflows. In contrast of the standard workflows, in which data between the jobs are exchanged in the form of files and the jobs are finished when they process the input data, data intensive workflows receive data organized in blocks which are streamed on inputs, analyze the data and produce stream output. Each job is active for a long period of time and can receive new data. In our previous research works we proposed the Open Grid Service Architecture for Data Mining (OGSA-DM), which is capable of executing data intensive workflows. According to our analysis, the current algorithms for scheduling workflows can't be applied on data intensive workflows because they produce unsatisfactory results and can't guarantee optimal solution. In this paper we propose new optimization and scheduling algorithm which is developed on the advantages of data intensive workflows. In several experiments we've shown that our proposed algorithm works and gives satisfactory results.

Solid state vibrational spectroscopic properties of morphine sulphate pentahydrate were studied combining experimental and theoretical approaches. Experimental studies involved a Fourier Transform infrared spectroscopic (FT IR) study of the title compound with the attenuated total reflection (ATR) technique. From theoretical side, a detailed study of the main possible constituents of the investigated molecular crystals: neutral morphine molecule and N-protonated morphine-H+ cation was carried out, employing meta hybrid density functional theory (DFT) approach with the M06-2X exchange-correlation functional, using 6-311G(dip) basis set. Potential energy surfaces (PES) of the studied systems were explored in details, paying particular attention to the intramolecular torsional flexibility. In both cases, four stable minima on the explored PES were located. Subsequently, harmonic vibrational analyses were carried out for each minimum, with the method of diagonalization of the mass-weighted Hessian matrices. Experimental data strongly suggest the presence of hydrogen sulphate anionic species in the investigated solid phase. Accounting for the stoichiometry of the compound, it is suggested that both neutral (unprotonated) morphine along with the N-protonated morphine-H+ cation could be present in the solid state as well. The agreement between experimental and theoretical spectra in the regions of appearance of bands due to morphine (or N-protonated morphine-H+ cation) intramolecular vibrational modes is remarkable. Thus, the present theoretical calculations enable solid theoretical support to the empirical assignments of the spectral bands and the present work could serve as a starting point for further studies of spectroscopic manifestations of morphine incorporation into specific drug dosage forms.

A rigorous but still feasible computational approach is implemented that aims to provide a fundamental theoretical basis for an in-depth understanding of vibrational spectroscopic properties of molecular systems relevant to atmospheric chemistry and climate science. The mentioned properties are, on the other hand, crucial in the context of experimental detection of the title molecular species and their noncovalently bonded clusters. Rotamers of formic acid are treated as particular example. Potential energy surface of free formic acid was thoroughly explored at Moller-Plesset perturbation theory level, including corrections up to the second order with a rather flexible basis set for orbital expansion (MP2/6–311++G(3df, 3pd)), as well as employing density functional tight binding approach (DFTB). Anharmonic O-H(D) stretching vibrational frequencies were calculated using several algorithms. It was found that MP2 level of theory leads to excellent agreement between theory and experiment without using any arbitrary scaling factor when the difference between O-H(D) stretching frequencies in the case of both rotamers is in question. DFTB performs significantly inferior to MP2 with this respect, while reproducing the absolute frequencies of individual rotamers rather well. Fully relaxed HCOH torsional potential was calculated as well and the frequencies of HCOH torsion in the cis- and trans-well were calculated either by solving the torsional Schrodinger equation variationally or by second-order perturbation theory. The agreement between theory and experiment is again excellent in cases when experimental data are available.

The problem of efficient resource management in large cloud data centres is well recognised in the cloud management community. With the rising demand for cloud services and expansion of the size and distribution of data centres, the repercussions of not taking into account all parameters of interest while allocating resources are becoming significant. Hence, one of the major issues today is how to reconcile between performance and energy efficiency so that customers can exploit the provided resources to their maximum while the provider still keeps a well balanced approach that ensures low cost and optimal power consumption. The main goal of this paper is to investigate what can be expected of performance optimisation allocation techniques from a power consumption perspective. The presented results show that careful design of resource allocation algorithms can lead towards solutions that are not only high performing, but are also good in efficient power consumption.

The popularity of Blockchain technology and the huge extent of its application, results with much ongoing research in different practical and scientific areas. Although still new and in experimenting phase, the Blockchain is being seen as a revolutionary solution, addressing modern technology concerns like decentralization, trust, identity, data ownership and data-driven decisions. At the same time, the world is facing an expansion in quantity and diversity of digital data that are generated by both users and machines. While actively searching for the best way to store, organize and process Big Data, the Blockchain technology comes in providing significant input. Its proposed solutions about decentralized management of private data, digital property resolution, IoT communication and public institutions' reforms are having significant impact on how Big Data may evolve. This paper presents the novel solutions associated with some of the Big Data areas that can be empowered by the Blockchain technology.

Modern research and education networks need to solve two major tasks: (1) providing seamless access to their users, and (2) support new scientific and collaborative applications that are becoming increasingly complex and dynamic in their scale, use of distributed resources, and required advanced networking services. Rapid deployment and automation of new network services provisioning is becoming difficult in large networks that incorporate different technologies and solutions. The task of providing seamless user experience in typically mobile and dynamically changing collaborative groups generates additional burdens for the configuration phases included in network provisioning. By introducing automation and enabling multipoint auto configuration of network devices, the Zero Touch Provisioning (ZTP) concept emerges as a possible alleviation of the complex network provisioning and infrastructure services deployment process. This paper investigates the characteristics of the ZTP model and discovers how ZTP can be used in order to enhance the services provided by the GEANT network and its associated National Research and Education Networks (NRENs) to the European research and education community. The future solution can be achieved by combining and enriching the existing provisioning models, solutions and practices available from different domains such as wireless networks, (complex) network management and operations services, and cloud based infrastructure services provisioning.

The need for customer-centric agile integrated environment offered in an on-demand self-service manner challenges the traditional R&E operations support systems. The service provider architecture proposed in this paper aims to satisfy end-user's requirements by providing a coordinated provisioning of virtualized resources through automation. Empowered by the establishment of open collaborative partnerships it offers expansion of the service catalog with multi-domain solutions based on standardized interoperability between R&E and commercial CSPs. The benefits of the approach are presented via a cloud based case study service that is transformed from a traditional silo to a business process modeled service with added values.