Taxonomy of P2P Applications

Peer-to-peer (p2p) networks have gained immense popularity in recent years and the number of services they provide continuously rises. Where p2p-networks were formerly known as file-sharing networks, p2p is now also used for services like VoIP and IPTV. With so many different p2p applications and services the need for a taxonomy framework rises. This paper describes the available p2p applications grouped by the services they provide. A taxonomy framework is proposed to classify old and recent p2p applications based on their characteristics

Constructing the Cool Wall: A Tool to Explore Teen Meanings of Cool

This paper describes the development and exploration of a tool designed to assist in investigating ‘cool’ as it applies to the design of interactive products for teenagers. The method involved the derivation of theoretical understandings of cool from literature that resulted in identification of seven core categories for cool, which were mapped to a hierarchy. The hierarchy includes having of cool things, the doing of cool activities and the being of cool. This paper focuses on a tool, the Cool Wall, developed to explore one specific facet of the hierarchy; exploring shared understanding of having cool things. The paper describes the development and construction of the tool, using a heavily participatory approach, and the results and analysis of a study carried out over 2 days in a school in the UK. The results of the study both provide clear insights into cool things and enable a refined understanding of cool in this context. Two additional studies are then used to identify potential shortcomings in the Cool Wall methodology. In the first study participants were able to populate a paper cool wall with anything they chose, this revealed two potential new categories of images and that the current set of images covered the majority of key themes. In the second study teenagers interpretations of the meaning of the images included in the Cool Wall were explored, this showed that the majority of meanings were as expected and a small number of unexpected interpretations provided some valuable insights

Classification of information systems research revisited: A keyword analysis approach

A number of studies have previously been conducted on keyword analysis in order to provide a comprehensive scheme to classify information systems (IS) research. However, these studies appeared prior to 1994, and IS research has clearly developed substantially since then with the emergence of areas such as electronic commerce, electronic government, electronic health and numerous others. Furthermore, the majority of European IS outlets - such as the European Journal of Information Systems and Information Systems Journal - were founded in the early 1990s, and keywords from these journals were not included in any previous work. Given that a number of studies have raised the issue of differences in European and North American IS research topics and approaches, it is arguable that any such analysis must consider sources from both locations to provide a representative and balanced view of IS classification. Moreover, it has also been argued that there is a need for further work in order to create a comprehensive keyword classification scheme reflecting the current state of the art. Consequently, the aim of this paper is to present the results of a keyword analysis utilizing keywords appearing in major peer-reviewed IS publications after the year 1990 through to 2007. This aim is realized by means of the two following objectives: (1) collect all keywords appearing in 24 peer reviewed IS journals after 1990; and (2) identify keywords not included in the previous IS keyword classification scheme. This paper also describes further research required in order to place new keywords in appropriate IS research categories. The paper makes an incremental contribution toward a contemporary means of classifying IS research. This work is important and useful for researchers in understanding the area and evolution of the IS field and also has implications for improving information search and retrieval activities

A framework for P2P application development

Although Peer-to-Peer (P2P) computing has become increasingly popular over recent years, there still exist only a very small number of application domains that have exploited it on a large scale. This can be attributed to a number of reasons including the rapid evolution of P2P technologies, coupled with their often-complex nature. This paper describes an implemented abstraction framework that seeks to aid developers in building P2P applications. A selection of example P2P applications that have been developed using this framework are also presented

Constructing the Cool Wall: A tool to explore teen meanings of cool

This paper describes the development and exploration of a tool designed to assist in investigating ‘cool’ as it applies to the design of interactive products for teenagers. The method involved the derivation of theoretical understandings of cool from literature that resulted in identification of seven core categories for cool, which were mapped to a hierarchy. The hierarchy includes having of cool things, the doing of cool activities and the being of cool. This paper focuses on a tool, the Cool Wall, developed to explore one specific facet of the hierarchy; exploring shared understanding of having cool things. The paper describes the development and construction of the tool, using a heavily participatory approach, and the results and analysis of three studies. The first study was carried out over 2 days in a school in the UK. The results of the study both provide clear insights into cool things and enable a refined understanding of cool in this context. Two additional studies are then used to identify potential shortcomings in the Cool Wall methodology. In the second study participants were able to populate a paper cool wall with anything they chose, this revealed two potential new categories of images and that the current set of images covered the majority of key themes. In the third study teenagers interpretations of the meaning of the images included in the Cool Wall were explored, this showed that the majority of meanings were as expected and a small number of unexpected interpretations provided some valuable insights

Localization in Long-range Ultra Narrow Band IoT Networks using RSSI

Internet of things wireless networking with long range, low power and low throughput is raising as a new paradigm enabling to connect trillions of devices efficiently. In such networks with low power and bandwidth devices, localization becomes more challenging. In this work we take a closer look at the underlying aspects of received signal strength indicator (RSSI) based localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI has been used for fingerprinting localization where RSSI measurements of GPS anchor nodes have been used as landmarks to classify other nodes into one of the GPS nodes classes. Through measurements we show that a location classification accuracy of 100% is achieved when the classes of nodes are isolated. When classes are approaching each other, our measurements show that we can still achieve an accuracy of 85%. Furthermore, when the density of the GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus improve the possibility of localizing nodes with an error less than 20m from 20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes is localized with an error of less than 50m in our experiment with non-optimized anchor node locations.Comment: Accepted in ICC 17. To be presented in IEEE International Conference on Communications (ICC), Paris, France, 201

A cloud-based tool for sentiment analysis in reviews about restaurants on TripAdvisor

The tourism industry has been promoting its products and services based on the reviews that people often write on travel websites like TripAdvisor.com, Booking.com and other platforms like these. These reviews have a profound effect on the decision making process when evaluating which places to visit, such as which restaurants to book, etc. In this contribution is presented a cloud based software tool for the massive analysis of this social media data (TripAdvisor.com). The main characteristics of the tool developed are: i) the ability to aggregate data obtained from social media; ii) the possibility of carrying out combined analyses of both people and comments; iii) the ability to detect the sense (positive, negative or neutral) in which the comments rotate, quantifying the degree to which they are positive or negative, as well as predicting behaviour patterns from this information; and iv) the ease of doing everything in the same application (data downloading, pre-processing, analysis and visualisation). As a test and validation case, more than 33.500 revisions written in English on restaurants in the Province of Granada (Spain) were analyse

Peer assessment and knowledge discovering in a community of learners

Thanks to the exponential growth of the Internet, Distance Education is becoming more and more strategic in many fields of daily life. Its main advantage is that students can learn through appropriate web platforms that allow them to take advantage of multimedia and interactive teaching materials, without constraints neither of time nor of space. Today, in fact, the Internet offers many platforms suitable for this purpose, such as Moodle, ATutor and others. Coursera is another example of a platform that offers different courses to thousands of enrolled students. This approach to learning is, however, posing new problems such as that of the assessment of the learning status of the learner in the case where there were thousands of students following a course, as is in Massive On-line Courses (MOOC). The Peer Assessment can therefore be a solution to this problem: evaluation takes place between peers, creating a dynamic in the community of learners that evolves autonomously. In this article, we present a first step towards this direction through a peer assessment mechanism led by the teacher who intervenes by evaluating a very small part of the students. Through a mechanism based on machine learning, and in particular on a modified form of K-NN, given the teacher’s grades, the system should converge towards an evaluation that is as similar as possible to the one that the teacher would have given. An experiment is presented with encouraging results