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Sensitivity of the health-related data and the focus on compliance and security has traditionally emphasized the need for centralized approach while implementing Electronic Health Records (EHR) systems. These one-institutional architectural designs are leading to fragmented and scattered pieces of valuable data across various data warehouses and silos. Interoperability challenges arise due to the absence of unified data management and exchange mechanisms making the social need for fundamental design changes bigger. The capability of a distributed ledger technology and blockchain to offer immutable, decentralized and cryptographically secured record of transactions throughout a peer-to-peer network can facilitate better collaboration and increased interoperability in the field of health and insurance information exchange processes. The paper examines different approaches and application of blockchain technology and identifies which implementations of components are more suitable and beneficial for the specific eco-system analyzed in the paper. This paper presents alternative way of dealing with information exchange across multiple stakeholders by justifying the use of decentralized approach, distributed access and solution how to comprehensively track and assemble health related data. We propose an architectural design and overview of a specific use case with focus on information exchange processes between health insurance providers and health care organizations, by using blockchain as an underlying technology. The architectural overview and data flows, backed up by sequence diagrams from specific use cases offered in this paper, can serve as a guide to the blockchain technology adoption and initial setup.

The Internet of Vehicles requires high bandwidth and low latency services to unleash the potential of fully connected vehicles. Thus, the offloading proposals that successfully manage massive real-time service requests from vehicle nodes are needed. In this paper, we analyse the dynamic resource management for intelligent vehicular networks based on Multi-access Edge Computing architecture services. Using a combination of CloudSim and SUMO simulators, we present a case study of infotainment services in the city centre of Alicante, in Spain, that shows a high degree of optimality both in service allocation and migration when considering dense urban environments.

Efficient resource management is crucial for balancing performance and energy consumption in large-scale data centres. In the case of additional requirements such as guaranteed resources and low communication latency, it is of great importance to implement not only an efficient initial placement algorithm, but also maximise consolidation by migration techniques, making sure that network performance is not sacrificed. In this paper, we introduce a hierarchical approach to migrations based on a combination of efficient packing algorithms and network communities. Results analysis shows the benefits of using a two-level approach where the combination of localised consolidation and network awareness improves both performance and energy efficiency, while maintaining low network hop distance.

Emerging models such as mobile edge computing provide the necessary characteristics for the deployment of Internet of Things applications by supplying the connected devices with local computing facilities essential for latency sensitive applications. One of the major issues of the underlying edge computing architecture is to cope with the device mobility that imposes dynamically changing network requirements. In this paper, we propose a resource management approach that aims to improve the location transparency and provide high quality of experience for end users by optimising latencies perceived when nodes are accessing services hosted on the edge of the network. By managing the virtualised computing resources based on the node location area information, the main objective of the approach is to minimise the network latency perceived by mobile nodes for both the initial allocation and the dynamic resource migration during the service lifetime while the requester node is changing location areas. The system is trying to achieve the most accurate 'follow me' service where the assigned resources closely follow the current mobile node location. The presented results show the effectiveness of the proposed solution in comparison to traditional resource management techniques on the macro and micro scale.

Hands-on experience and training related to the latest cyberthreats and best practices, augmented with real-life examples and scenarios is very important for aspiring cybersecurity specialists and IT professionals in general. However, this is not always possible either because of time, financial or technological constraints. For cybersecurity exercises to be effective they must be well prepared, the necessary equipment installed, and an appropriate level of isolation configured, preventing inter-user interference, and protecting the integrity of the platform itself. In recent years there have been numerous cybersecurity training systems developed that aim to solve these problems. They can either be used as cloud or self-hosted applications. These solutions vary in their level of sophistication and ease-of-use, but they all share a single goal, to better educate the cyber community about the most common vulnerabilities and how to overcome them. The aim of this paper is to survey and analyze popular cybersecurity training systems currently available, and to offer a taxonomy which would aid in their classification and help crystalize their possibilities and limitations, thus supporting the decision-making process.

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.

The ongoing trends in cloud computing demonstrate increasing need for efficient, yet economical data centers. Thus, recently the research community has focused its efforts on frameworks for optimised usage of the available resources that will result with energy-efficient and highly effective data centers. Toward this goal, in this paper we present a community-based framework for virtual machine placement inside a cloud data center. The framework is based on the complex network structural property of grouping tightly coupled nodes, and a matching process that maps virtual to physical communities while employing different optimisation functions on different hierarchy levels. The presented simulation results of the framework application reflect its high usage potential achieved by improvement in communication efficiency and reduced power consumption compared to the traditional heuristics.

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.

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 goal of this paper is to propose some software engineering practices and principles that could increase the quality of scientific applications. Since standard principles of software engineering cannot fully engage in enhancing the development process of such applications, finding the right principles and their combination that will improve the quality is real challenge for software engineers. In order to provide more realistic representation of problems in the field of scientific high-performance computing, we conducted a survey where developers of scientific applications in the HP-SEE project answered some key questions about testing methods and conventions they used. Analysis of the results of the responses was major indicator of quality deficiencies in the high-performance scientific software development and that helped us to discern the possible improvements that need to be added in the planning, development and particularly in the verification phases of the software life cycle.

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.

Under the auspices of a DAAD funded educational project, a subproject devoted to different aspects of teaching the Java programming language started several years ago. The initial intention of the subproject was to attract members of the subproject to prepare some teaching ma- terials for teaching essentials of the Java programming language. During the last two years, some advanced Java topics have been selected and appropriate teaching materials have been produced. The available pool of common teaching materials can be used in a wide range of university courses in participating countries. In this paper we share some of the results and experiences collected dur- ing the subproject that come from intensive use of the prepared teaching materials for a variety of Java topics in different countries and universities.