Future Internet, Volume 8, Issue 2 (June 2016) – 19 articles

Since the turn of the 21st century, we have seen a surge of studies on the state of U.S. education addressing issues such as cost, graduation rates, retention, achievement, engagement, and curricular outcomes. There is an expectation that graduates should be able to enter the workplace equipped to take on complex and “messy” or ill-structured problems as part of their professional and everyday life. In the context of online learning, we have identified two key issues that are elusive (hard to capture and make visible): learning with ill-structured problems and the interaction of social and individual learning. We believe that the intersection between learning and analytics has the potential, in the long-term, to minimize the elusiveness of deep learning. A proposed analytics model is described in this article that is meant to capture and also support further development of a learner’s reflective sensemaking. Full article

The aim of the study was deepening the knowledge of livestock innovations knowledge on small-scale farms in developing countries. First, we developed a methodology focused on identifying potential appropriate livestock innovations for smallholders and grouped them in innovation areas, defined as a set of well-organized practices with a business purpose. Finally, a process management program (PMP) was evaluated according to the livestock innovation level and viability of the small-scale farms. Logistic regression was used to evaluate the impact of PMP on the economic viability of the farm. Information from 1650 small-scale livestock farms in Mexico was collected and the innovations were grouped in five innovation areas: A1. Management, A2. Feeding, A3. Genetic, A4. Reproduction and A5. Animal Health. The resulting innovation level in the system was low at 45.7% and heterogeneous among areas. This study shows the usefulness of the methodology described and confirms that implementing a PMP allows improving the viability an additional 21%, due to a better integration of processes, resulting in more efficient management. Full article

Emerging technologies such as Software-Defined Networks (SDN) and Network Function Virtualization (NFV) promise to address cost reduction and flexibility in network operation while enabling innovative network service delivery models. However, operational network service delivery solutions still need to be developed that actually exploit these technologies, especially at the multi-provider level. Indeed, the implementation of network functions as software running over a virtualized infrastructure and provisioned on a service basis let one envisage an ecosystem of network services that are dynamically and flexibly assembled by orchestrating Virtual Network Functions even across different provider domains, thereby coping with changeable user and service requirements and context conditions. In this paper we propose an approach that adopts Service-Oriented Architecture (SOA) technology-agnostic architectural guidelines in the design of a solution for orchestrating and dynamically chaining Virtual Network Functions. We discuss how SOA, NFV, and SDN may complement each other in realizing dynamic network function chaining through service composition specification, service selection, service delivery, and placement tasks. Then, we describe the architecture of a SOA-inspired NFV orchestrator, which leverages SDN-based network control capabilities to address an effective delivery of elastic chains of Virtual Network Functions. Preliminary results of prototype implementation and testing activities are also presented. The benefits for Network Service Providers are also described that derive from the adaptive network service provisioning in a multi-provider environment through the orchestration of computing and networking services to provide end users with an enhanced service experience. Full article

A smart city is an environment where a pervasive, multi-service network is employed to provide citizens improved living conditions as well as better public safety and security. Advanced communication technologies are essential to achieve this goal. In particular, an efficient and reliable communication network plays a crucial role in providing continue, ubiquitous, and reliable interconnections among users, smart devices, and applications. As a consequence, wireless networking appears as the principal enabling communication technology despite the necessity to face severe challenges to satisfy the needs arising from a smart environment, such as explosive data volume, heterogeneous data traffic, and support of quality of service constraints. An interesting approach for meeting the growing data demand due to smart city applications is to adopt suitable methodologies to improve the usage of all potential spectrum resources. Towards this goal, a very promising solution is represented by the Cognitive Radio technology that enables context-aware capability in order to pursue an efficient use of the available communication resources according to the surrounding environment conditions. In this paper we provide a review of the characteristics, challenges, and solutions of a smart city communication architecture, based on the Cognitive Radio technology, by focusing on two new network paradigms—namely, Heterogeneous Network and Machines-to-Machines communications—that are of special interest to efficiently support smart city applications and services. Full article

The concept of competence, which emerged during the reform of computer engineering degrees, has not brought benefits to companies when attempting to select the most suitable candidates for their jobs. This article aims to show some of the research that has been conducted to determine why companies have not found these skills useful and how both can be aligned. Finally, we show the development of an Expert System that will enable companies to select the most suitable candidates for their jobs, considering personal and social skills, along with technical knowledge. This prototype will serve as a basis to align the competencies defined in the curricula with professional requirements, thus allowing a true alignment between degree courses and the needs of professional companies. Full article

For many individuals and organizations, cyber-insurance is the most practical and only way of handling a major financial impact of an information security event. However, the cyber-insurance market suffers from the problem of information asymmetry, lack of product diversity, illiquidity, high transaction cost, and so on. On the other hand, in theory, capital market-based financial instruments can provide a risk transfer mechanism with the ability to absorb the adverse impact of an information security event. Thus, this article addresses the limitations in the cyber-(re)insurance markets with a set of capital market-based financial instruments. This article presents a set of information security derivatives, namely options, vanilla options, swap, and futures that can be traded at an information security prediction market. Furthermore, this article demonstrates the usefulness of information security derivatives in a given scenario and presents an evaluation of the same in comparison with cyber-insurance. In our analysis, we found that the information security derivatives can at least be a partial solution to the problems in the cyber-insurance markets. The information security derivatives can be used as an effective tool for information elicitation and aggregation, cyber risk pricing, risk hedging, and strategic decision making for information security risk management. Full article

The many decisions that people make about what to pay attention to online shape the spread of information in online social networks. Due to the constraints of available time and cognitive resources, the ease of discovery strongly impacts how people allocate their attention to social media content. As a consequence, the position of information in an individual’s social feed, as well as explicit social signals about its popularity, determine whether it will be seen, and the likelihood that it will be shared with followers. Accounting for these cognitive limits simplifies mechanics of information diffusion in online social networks and explains puzzling empirical observations: (i) information generally fails to spread in social media and (ii) highly connected people are less likely to re-share information. Studies of information diffusion on different social media platforms reviewed here suggest that the interplay between human cognitive limits and network structure differentiates the spread of information from other social contagions, such as the spread of a virus through a population. Full article

In the last 20 years, the convergence of different factors—the rise of the complexity of science, the “data deluge” and the advances in information technologies—triggered a paradigm shift in the way we understand complex social systems and their evolution. Beyond shedding new light onto social dynamics, the emerging research area of Computational Social Science (CSS) is providing a new rationale for a more scientifically-grounded and effective policy design. The paper discusses the opportunities potentially deriving from the intersection between policy design issues and CSS methods. After a general introduction to the limits of traditional policy-making and a brief review of the most promising CSS methodologies, the work deals with way in which the insights potentially offered by CSS can concretely flow in policy choices. The attention is focused, to this end, on the legal mechanisms regulating the formulation and the evaluation of public policies. Our goal is two-fold: sketch how the project of a “smart society” is connected to the evolution of social sciences and emphasize the need for change in the way in which public policies are conceived of, designed and implemented. Full article

Internet of Things (IoT) seems a viable way to enable the Smart Cities of the future. iNUIT (Internet of Things for Urban Innovation) is a multi-year research program that aims to create an ecosystem that exploits the variety of data coming from multiple sensors and connected objects installed on the scale of a city, in order to meet specific needs in terms of development of new services (physical security, resource management, etc.). Among the multiple research activities within iNUIT, we present two projects: SmartCrowd and OpEc. SmartCrowd aims at monitoring the crowd’s movement during large events. It focuses on real-time tracking using sensors available in smartphones and on the use of a crowd simulator to detect possible dangerous scenarios. A proof-of-concept of the application has been tested at the Paléo Festival (Switzerland) showing the feasibility of the approach. OpEc (Optimisation de l’Eclairage public) aims at using IoT to implement dynamic street light management and control with the goal of reducing street light energy consumption while guaranteeing the same level of security of traditional illumination. The system has been tested during two months in a street in St-Imier (Switzerland) without interruption, validating its stability and resulting in an overall energy saving of about 56%. Full article

Cloud computing systems enable clients to rent and share computing resources of third party platforms, and have gained widespread use in recent years. Numerous varieties of mobile, small-scale devices such as smartphones, red e-health devices, etc., across users, are connected to one another through the massive internetwork of vastly powerful servers on the cloud. While mobile devices store “private information” of users such as location, payment, health data, etc., they may also contribute “semi-public information” (which may include crowdsourced data such as transit, traffic, nearby points of interests, etc.) for data analytics. In such a scenario, a mobile device may seek to obtain the result of a computation, which may depend on its private inputs, crowdsourced data from other mobile devices, and/or any “public inputs” from other servers on the Internet. We demonstrate a new method of delegating real-world computations of resource-constrained mobile clients using an encrypted program known as the garbled circuit. Using the garbled version of a mobile client’s inputs, a server in the cloud executes the garbled circuit and returns the resulting garbled outputs. Our system assures privacy of the mobile client’s input data and output of the computation, and also enables the client to verify that the evaluator actually performed the computation. We analyze the complexity of our system. We measure the time taken to construct the garbled circuit as well as evaluate it for varying number of servers. Using real-world data, we evaluate our system for a practical, privacy preserving search application that locates the nearest point of interest for the mobile client to demonstrate feasibility. Full article

Interoperability and social implication are two current challenges in the digital library (DL) context. To resolve the problem of interoperability, our work aims to find a relationship between the main metadata schemas. In particular, we want to formalize knowledge through the creation of a metadata taxonomy built with the analysis and the integration of existing schemas associated with DLs. We developed a method to integrate and combine Instagram metadata and hashtags. The final result is a taxonomy, which provides innovative metadata with respect to the classification of resources, as images of Instagram and the user-generated content, that play a primary role in the context of modern DLs. The possibility of Instagram to localize the photos inserted by users allows us to interpret the most relevant and interesting informative content for a specific user type and in a specific location and to improve access, visibility and searching of library content. Full article

In recent years, the interest in delay/disruption tolerant networking (DTN) is growing as a means of communication in times of disaster. To ensure that a DTN works well in an emergency, it is desirable to promote general use of the DTN, so that it will also be used in normal times. Since the DTN uses mobile terminals and vehicles, which are not dedicated network devices, as relay nodes, the routing method should be such that it does not impose a large processing load on relay nodes. This paper considers use of a DTN for a day-to-day service of delivering content to a specific area and proposes a new routing method that is based on information about the routes of fixed-route traveling nodes, such as public transportation vehicles. The destination of a bundle is specified not by a terminal identifier, but by an area, which is identified by its location information. This paper presents an outbound-type bundle protocol, which is used by relay nodes when they have received a forwarding-bundle request from a sending terminal and try to determine whether the bundle can reach its destination area. Using simulation, the superiority of the proposed routing was confirmed by comparing it to existing routing methods in terms of the bundle arrival rate and factors that affect the network load, such as the number of bundle copies, the number of hops and the maximum required buffer size. Full article

Social norms have traditionally been difficult to quantify. In any particular society, their sheer number and complex interdependencies often limit a system-level analysis. One exception is that of the network of norms that sustain the online Wikipedia community. We study the fifteen-year evolution of this network using the interconnected set of pages that establish, describe, and interpret the community’s norms. Despite Wikipedia’s reputation for ad hoc governance, we find that its normative evolution is highly conservative. The earliest users create norms that both dominate the network and persist over time. These core norms govern both content and interpersonal interactions using abstract principles such as neutrality, verifiability, and assume good faith. As the network grows, norm neighborhoods decouple topologically from each other, while increasing in semantic coherence. Taken together, these results suggest that the evolution of Wikipedia’s norm network is akin to bureaucratic systems that predate the information age. Full article

Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a collection of software systems that have been developed to coexist and evolve together. The stakeholders of such a system need a variety of models to give them a perspective of the possibilities of the system, to evaluate specific quality attributes, and to extend the system. A powerful representation when building or using software ecosystems is the use of architectural models, which describe the structural aspects of such a system. These models have value for security and compliance, are useful to build new systems, can be used to define service contracts, find where quality factors can be monitored, and to plan further expansion. We have described a cloud ecosystem in the form of a pattern diagram where its components are patterns and reference architectures. A pattern is an encapsulated solution to a recurrent problem. We have recently expanded these models to cover fog systems and containers. Fog Computing is a highly-virtualized platform that provides compute, storage, and networking services between end devices and Cloud Computing Data Centers; a Software Container provides an execution environment for applications sharing a host operating system, binaries, and libraries with other containers. We intend to use this architecture to answer a variety of questions about the security of this system as well as a reference to design interacting combinations of heterogeneous components. We defined a metamodel to relate security concepts which is being expanded. Full article

This paper introduces a method for assessing the influence of Twitter accounts of central e-government agencies. It first stresses the importance of activity and popularity of the e-government accounts, and also the importance of community formation among followers-citizens, as the two main stages of e-government adoption. The proposed approach combines activity and popularity of the accounts and followers’ community characteristics in a ranking system, using an idea originally introduced to measure blogosphere authority. A Twitter Authority Index is produced. The method is demonstrated through an extended example: 56 Twitter accounts of ministries of EU countries are sorted according to their indexes in the proposed ranking system. Detailed values for the ministries’ accounts and average values for the countries that the ministries belong to are reported and commented. Full article

Outdoor leisure activities are important for public health as well as family cohesiveness, yet environmental factors may easily affect someone’s ability to participate in such activities. We explored this with a focus on the social web-based treasure hunt game called Geocaching. We collected data on all US and Canadian geocaches from OpenCaching.com and conducted an online survey with twenty geocachers as a follow-up to our data analysis. Data analysis showed that geocaches were more often found in areas that were wealthier, better educated, younger, and more urban, and had higher population density and better weather. Survey results showed similar trends: Most people actively thought about where they would cache and tried to minimize risks, despite cache hiders thinking less about these concerns. These results further emphasize the importance of environmental factors when it comes to participation in outdoor activities and leads to Human–Computer Interaction design implications for location-based online social activities. Full article

Every day, each active social network user produces and shares texts, images and videos. While developers can access such data through application programming interfaces (APIs) for creating games, visualizations and routines, end users have less control on such information. Their access is mediated by the social application features, which limits them in combining sources, filtering results and performing actions on groups of elements. In order to fill this gap, we introduce FaceMashup, an end user development (EUD) environment supporting the manipulation of the Facebook graph. We describe the tool interface, documenting the choices we made during the design iterations. Data types are represented through widgets containing user interface (UI) elements similar to those used in the social network application. Widgets can be connected with each other with the drag and drop of their inner fields, and the application updates their content. Finally, we report the results of a user-test on the FaceMashup prototype, which shows a good acceptance of the environment by end-users. Full article

Users share vast amounts of personal information online, but are they fully aware of what information they are sharing and with whom? In this paper, we focused on Facebook apps and set out to understand how concerned users are about privacy and how well-informed they are about what personal data apps can access. We found that initially, subjects were generally under-informed about what data apps could access from their profiles. After viewing additional information about these permissions, subjects’ concern about privacy on Facebook increased. Subjects’ understanding of what data apps were able to access increased, although even after receiving explicit information on the topic, many subjects still did not fully understand the extent to which apps could access their data. Full article

Feature extraction methods have been used to extract location features for indoor positioning in wireless local area networks. However, existing methods, such as linear discriminant analysis and principal component analysis, all suffer from the multimodal property of signal distribution. This paper proposes a novel method, based on enhanced local fisher discriminant analysis (LFDA). First, LFDA is proposed to extract discriminative location features. It maximizes between-class separability while preserving within-class local structure of signal space, thereby guaranteeing maximal discriminative information involved in positioning. Then, the generalization ability of LFDA is further enhanced using signal perturbation, which generates more number of representative training samples. Experimental results in realistic indoor environment show that, compared with previous feature extraction methods, the proposed method reduces the mean and standard deviation of positing error by 23.9% and 33.0%, respectively. Full article