Future Internet, Volume 8, Issue 4 (December 2016) – 10 articles

Climate and weather realizations are essential inputs for simulating crop growth and yields to analyze the risks associated with future conditions. To simplify the procedure of generating weather realizations and make them available over the Internet, we implemented novel mechanisms for providing weather generators as web services, as well as a mechanism for sharing identical weather realizations given a climatological information. A web service for preparing long-term climate data was implemented based on an international standard, Sensor Observation Service (SOS). The weather generator services, which are the core components of the framework, analyze climatological data, and can take seasonal climate forecasts as inputs for generating weather realizations. The generated weather realizations are encoded in a standard format, which are ready for use to crop modeling. All outputs are generated in SOS standard, which broadens the extent of data sharing and interoperability with other sectoral applications, e.g., water resources management. These services facilitate the development of other applications requiring input weather realizations, as these can be obtained easily by just calling the service. The workload of analysts related to data preparation and handling of legacy weather generator programs can be reduced. The architectural design and implementation presented here can be used as a prototype for constructing further services on top of an interoperable sensor network system. Full article

The multi-focus image fusion method is used in image processing to generate all-focus images that have large depth of field (DOF) based on original multi-focus images. Different approaches have been used in the spatial and transform domain to fuse multi-focus images. As one of the most popular image processing methods, dictionary-learning-based spare representation achieves great performance in multi-focus image fusion. Most of the existing dictionary-learning-based multi-focus image fusion methods directly use the whole source images for dictionary learning. However, it incurs a high error rate and high computation cost in dictionary learning process by using the whole source images. This paper proposes a novel stochastic coordinate coding-based image fusion framework integrated with local density peaks. The proposed multi-focus image fusion method consists of three steps. First, source images are split into small image patches, then the split image patches are classified into a few groups by local density peaks clustering. Next, the grouped image patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP) algorithm is used to carry out sparse representation. After the three steps, the obtained sparse coefficients are fused following the max L1-norm rule. The fused coefficients are inversely transformed to an image by using the learned dictionary. The results and analyses of comparison experiments demonstrate that fused images of the proposed method have higher qualities than existing state-of-the-art methods. Full article

As the Internet becomes larger in scale, more complex in structure and more diversified in traffic, the number of crimes that utilize computer technologies is also increasing at a phenomenal rate. To react to the increasing number of computer crimes, the field of computer and network forensics has emerged. The general purpose of network forensics is to find malicious users or activities by gathering and dissecting firm evidences about computer crimes, e.g., hacking. However, due to the large volume of Internet traffic, not all the traffic captured and analyzed is valuable for investigation or confirmation. After analyzing some existing network forensics methods to identify common shortcomings, we propose in this paper a new network forensics method that uses a combination of network vulnerability and network evidence graph. In our proposed method, we use vulnerability evidence and reasoning algorithm to reconstruct attack scenarios and then backtrack the network packets to find the original evidences. Our proposed method can reconstruct attack scenarios effectively and then identify multi-staged attacks through evidential reasoning. Results of experiments show that the evidence graph constructed using our method is more complete and credible while possessing the reasoning capability. Full article

On the high-speed connections of the Internet or computer networks, the IP (Internet Protocol) packet traffic passing through the network is extremely high, and that makes it difficult for network monitoring and attack detection applications. This paper reviews methods to find the high-occurrence-frequency elements in the data stream and applies the most efficient methods to find Hot-IPs that are high-frequency IP addresses of IP packets passing through the network. Fast finding of Hot-IPs in the IP packet stream can be effectively used in early detection of DDoS (Distributed Denial of Service) attack targets and spreading sources of network worms. Research results show that the Count-Min method gives the best overall performance for Hot-IP detection thanks to its low computational complexity, low space requirement and fast processing speed. We also propose an early detection model of DDoS attack targets based on Hot-IP finding, which can be deployed on the target network routers. Full article

The present grievous tuberculosis situation can be improved by efficient case management and timely follow-up evaluations. With the advent of digital technology, this can be achieved through quick summarization of the patient-centric data. The aim of our study was to assess the effectiveness of the ODK Scan paper-to-digital system during a testing period of three months. A sequential, explanatory mixed-method research approach was employed to elucidate technology use. Training, smartphones, the application and 3G-enabled SIMs were provided to the four field workers. At the beginning, baseline measures of the data management aspects were recorded and compared with endline measures to determine the impact of ODK Scan. Additionally, at the end of the study, users’ feedback was collected regarding app usability, user interface design and workflow changes. A total of 122 patients’ records were retrieved from the server and analysed in terms of quality. It was found that ODK Scan recognized 99.2% of multiple choice fill-in bubble responses and 79.4% of numerical digit responses correctly. However, the overall quality of the digital data was decreased in comparison to manually entered data. Using ODK Scan, a significant time reduction is observed in data aggregation and data transfer activities, but data verification and form-filling activities took more time. Interviews revealed that field workers saw value in using ODK Scan, but they were more concerned about the time-consuming aspects of the use of ODK Scan. Therefore, it is concluded that minimal disturbance in the existing workflow, continuous feedback and value additions are the important considerations for the implementing organization to ensure technology adoption and workflow improvements. Full article

The Senior Living Lab (SLL) is a transdisciplinary research platform created by four Universities that aims at promoting ageing well at home through the co-creation of innovative products, services and practices with older adults. While most living labs for ageing well are focused on Information and Communication Technologies (ICTs), this social laboratory adopts a transdisciplinary approach, bringing together designers, economists, engineers and healthcare professionals to develop multiple forms of social innovation using participatory methods. The SLL is based on an ecological approach, connecting professionals and users in a cooperative network and involving all of the stakeholders concerned with ageing well, such as existing associations, business entities and policy-makers. Three main themes for the co-design of products and services were identified at the beginning of the SLL conception, each sustained by a major business partner: healthy nutrition to cope with frailty, improved autonomous mobility to foster independence and social communication to prevent isolation. This article shows the innovative transdisciplinary approach of the SLL and discusses the particular challenges that emerged during the first year of its creation, investigating the role of ICTs when designing products and services for older adults. Full article

Bitcoin (BTC) is often cited as Libertarian. However, the technology underpinning Bitcoin, blockchain, has properties that make it ideally suited to Socialist paradigms. Current literature supports the Libertarian viewpoint by focusing on the ability of Bitcoin to bypass central authority and provide anonymity; rarely is there an examination of blockchain technology’s capacity for decentralised transparency and auditability in support of a Socialist model. This paper conducts a review of the blockchain, Libertarianism, and Socialist philosophies. It then explores Socialist models of public ownership and looks at the unique cooperative properties of blockchain that make the technology ideal for supporting Socialist societies. In summary, this paper argues that blockchain technologies are not just a Libertarian tool, they also enhance Socialist forms of governance. Full article

Currently, the field of smart-* (home, city, health, tourism, etc.) is naturally heterogeneous and multimedia oriented. In such a domain, there is an increasing usage of heterogeneous mobile devices, as well as captors transmitting data (IoT). They are highly connected and can be used for many different services, such as to monitor, to analyze and to display information to users. In this context, data management and adaptation in real time are becoming a challenging task. More precisely, at one time, it is necessary to handle in a dynamic, intelligent and transparent framework various data provided by multiple devices with several modalities. This paper presents a Kali-Smart platform, which is an autonomic semantic-based context-aware platform. It is based on semantic web technologies and a middleware providing autonomy and reasoning facilities. Moreover, Kali-Smart is generic and, as a consequence, offers to users a flexible infrastructure where they can easily control various interaction modalities of their own situations. An experimental study has been made to evaluate the performance and feasibility of the proposed platform. Full article

In order to develop a Supercomputing Cloud Platform (SCP) prototype system using Service-Oriented Architecture (SOA) and Petri nets, we researched some technologies for Web service composition. Specifically, in this paper, we propose a reliability calculation method for Web service compositions, which uses Fuzzy Reasoning Colored Petri Net (FRCPN) to verify the Web service compositions. We put forward a definition of semantic threshold similarity for Web services and a formal definition of FRCPN. We analyzed five kinds of production rules in FRCPN, and applied our method to the SCP prototype. We obtained the reliability value of the end Web service as an indicator of the overall reliability of the FRCPN. The method can test the activity of FRCPN. Experimental results show that the reliability of the Web service composition has a correlation with the number of Web services and the range of reliability transition values. Full article

Smartness in contemporary society implies the use of massive data to improve the experience of people with connected services and products. The use of big data to collect information about people’s behaviours opens a new concept of “user-centred design” where users are remotely monitored, observed and profiled. In this paradigm, users are considered as sources of information and their participation in the design process is limited to a role of data generators. There is a need to identify methodologies that actively involve people and communities at the core of ecosystems of interconnected products and services. Our contribution to designing for social innovation in ecosystems relies on developing new methods and approaches to transform data-driven design using a participatory and co-creative data-enabled design approach. To this end, we present one of the methods we have developed to design “smart” systems called Experiential Design Landscapes (EDL), and two sample projects, Social Stairs and [Y]our Perspective. Social Stairs faces the topic of behaviour change mediated by sensing technologies. [Y]our Perspective is a social platform to sustain processes of deliberative democracy. Both projects exemplify our approach to data-enabled design as a social proactive participatory design approach. Full article