Reflective mobile middleware for context-aware applications

The increasing popularity of mobile devices, such as mobile phones and personal digital assistants, and advances in wireless networking technologies, are enabling new classes of applications that present challenging problems to application designers. Applications have to be aware of, and adapt to, variations in the execution context, such as fluctuating network bandwidth and decreasing battery power, in order to deliver a good quality of service to their users. We argue that building applications directly on top of the network operating system would be extremely tedious and error-prone, as application developers would have to deal with these issues explicitly, and would consequently be distracted from the actual requirements of the application they are building. Rather, a middleware layered between the network operating system and the application should provide application developers with abstractions and mechanisms to deal with them. We investigate the principle of reflection and demonstrate how it can be used to support context-awareness and dynamic adaptation to context changes. We offer application engineers an abstraction of middleware as a dynamically customisable service provider, where each service can be delivered using different policies when requested in different contexts. Based on this abstraction, current middleware behaviour, with respect to a particular application, is reified in an application profile, and made accessible to the application for run-time inspection and adaptation. Applications can use the meta-interface that the middleware provides to change the information encoded in their profile, thus tailoring middleware behaviour to the user's needs. However, while doing so, conflicts may arise; different users may have different quality-of-service needs, and applications, in an attempt to full these needs, may customise middleware behaviour in conflicting ways. These conflicts have to be resolved in order to allow applications to come to an agreement, and thus be able to engage successful collaborations. We demonstrate how microeconomic techniques can be used to treat these kinds of conflicts. We offer an abstraction of the mobile setting as an economy, where applications compete to have a service delivered according to their quality-of-service needs. We have designed a mechanism where middleware plays the role of the auctioneer, collecting bids from the applications and delivering the service using the policy that maximises social welfare; that is, the one that delivers, on average, the best quality-of-service. We formalise the principles discussed above, namely reflection to support context-awareness and microeconomic techniques to support conflict resolution. To demonstrate their effectiveness in fostering the development of context-aware applications, we discuss a middleware architecture and implementation (CARISMA) that embed these principles, and report on performance and usability results obtained during a thorough evaluation stage

Journal of Internet Services and Applications manuscript No. (will be inserted by the editor) Middleware for Social Computing: A

Abstract Social computing broadly refers to supporting social behaviours using computational systems. In the last decade, the advent of Web 2.0 and its social networking services, wikis, blogs, and social bookmarking has revolutionised social computing, creating new online contexts within which people interact socially (social networking). With the pervasiveness of mobile devices and embedded sensors, we stand at the brink of another major revolution, where the boundary between online and offline social behaviours blurs, providing opportunities for (re)defining social conventions and contexts once again. But opportunities come with challenges: can middleware foster the engineering of social software? We identify three societal grand challenges that are likely to drive future research in social computing and elaborate on how the middleware community can help address them

Measuring Similarity in Large-Scale Folksonomies

Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. Unlike\ud taxonomies, which overimpose a hierarchical categorisation of content, folksonomies enable end-users to freely create and choose the categories (in this case, tags) that best\ud describe some content. However, as tags are informally de-\ud fined, continually changing, and ungoverned, social tagging\ud has often been criticised for lowering, rather than increasing, the efficiency of searching, due to the number of synonyms, homonyms, polysemy, as well as the heterogeneity of\ud users and the noise they introduce. To address this issue, a\ud variety of approaches have been proposed that recommend\ud users what tags to use, both when labelling and when looking for resources. As we illustrate in this paper, real world\ud folksonomies are characterized by power law distributions\ud of tags, over which commonly used similarity metrics, including the Jaccard coefficient and the cosine similarity, fail\ud to compute. We thus propose a novel metric, specifically\ud developed to capture similarity in large-scale folksonomies,\ud that is based on a mutual reinforcement principle: that is,\ud two tags are deemed similar if they have been associated to\ud similar resources, and vice-versa two resources are deemed\ud similar if they have been labelled by similar tags. We offer an efficient realisation of this similarity metric, and assess its quality experimentally, by comparing it against cosine similarity, on three large-scale datasets, namely Bibsonomy, MovieLens and CiteULike

Social contribution settings and newcomer retention in humanitarian crowd mapping

Organisers of crowd mapping initiatives seek to identify practices that foster an active contributor community. Theory suggests that social contribution settings can provide important support functions for newcomers, yet to date there are no empirical studies of such an effect. We present the first study that evaluates the relationship between colocated practice and newcomer retention in a crowd mapping community, involving hundreds of first-time participants. We find that certain settings are associated with a significant increase in newcomer retention, as are regular meetings, and a greater mix of experiences among attendees. Factors relating to the setting such as food breaks and technical disruptions have comparatively little impact. We posit that successful social contribution settings serve as an attractor: they provide opportunities to meet enthusiastic contributors, and can capture prospective contributors who have a latent interest in the practice

Effective Retrieval of Resources in Folksonomies Using a New Tag Similarity Measure

Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. However, as tags are informally defined, continually changing, and ungoverned, it has often been criticised for lowering, rather than increasing, the efficiency of searching. To address this issue, a variety of approaches have been proposed that recommend users what tags to use, both when labeling and when looking for resources. These techniques work well in dense folksonomies, but they fail to do so when tag usage exhibits a power law distribution, as it often happens in real-life folksonomies. To tackle this issue, we propose an approach that induces the creation of a dense folksonomy, in a fully automatic and transparent way: when users label resources, an innovative tag similarity metric is deployed, so to enrich the chosen tag set with related tags already present in the folksonomy. The proposed metric, which represents the core of our approach, is based on the mutual reinforcement principle. Our experimental evaluation proves that the accuracy and coverage of searches guaranteed by our metric are higher than those achieved by applying classical metrics.Comment: 6 pages, 2 figures, CIKM 2011: 20th ACM Conference on Information and Knowledge Managemen

The role of the Big Geographic Sort in Online News Circulation among U.S. Reddit Users

Past research has attributed the circulation of online news to two main factors—individual characteristics (e.g., a person’s information literacy) and social media efects (e.g., algorithmmediated information difusion)—and has overlooked a third one: the critical mass created by the ofine self-segregation of Americans into like-minded geographical regions such as states (a phenomenon called ‘The Big Sort’). We hypothesized that this latter factor matters for the online spreading of news not least because online interactions, despite having the potential of being global, end up being localized: interaction probability is known to rapidly decay with distance. Upon analysis of more than 8M Reddit comments containing news links spanning four years, from January 2016 to December 2019, we found that Reddit did not work as an ‘hype machine’ for news (as opposed to what previous work reported for other platforms, circulation was not mainly caused by platform-facilitated network efects). Rather, news circulation in Reddit worked as a supply-and-demand system: news items scaled linearly with the number of users in each state (with a scaling exponent β ≈ 1, and a goodness of ft R2 ≈ 0.95). Furthermore, deviations from such a universal pattern were best explained by state-level personality and cultural factors (R2 ≈ {0.12, 0.39}), rather than socioeconomic conditions (R2 ≈ {0.15, 0.29}) or political characteristics (R2 ≈ {0.06, 0.21}). Higher-than-expected circulation of any type of news was found in states characterised by residents who tend to be less diligent in terms of their personality (low in conscientiousness) and by loose cultures understating the importance of adherence to norms (low in cultural tightness). Interestingly, the combination of those factors with low levels of education was then associated with the circulation of a particular type of news, that is, misinformation. These results suggest that online interactions are geographically bounded and, as such, news circulation cannot be studied purely as an Internet phenomenon but should be grounded into a user’s ofine cultural environment, which has become increasingly segregated over the decades, and is admittedly hard to change

Rwandan Pay-As-You-Go Solar Home System User Payment Behavioural Types

The pay-as-you-go (PAYGo) model is now the principal way through which solar home systems (SHSs) are distributed in Sub-Saharan Africa. By alleviating the upfront cost and providing flexible payment schemes, the PAYGo model helps tackle what is still the main barrier for SHS adoption-i.e., affordability. However, the scheme’s design and evaluation are still largely guided by assumptions on user behaviour. This work provides a first evidence-based look into SHS PAYGo user payment patterns and behaviours, by using payment records of over 32,000 Rwandan SHS users. Three clustering algorithms are implemented to conduct a customer segmentation, employing an ensemble validation method which facilitates qualitative oversight. The analysis reveals five user payment behavioural profiles which serve to aid improvement in the current PAYGo model design

La historia de la ciencia como herramienta para la enseñanza de física en secundaria : un ejemplo en calor y temperatura

In this work we suggest and analyze some stages of a course on heat and temperature which knowledge of the past of the ideas and the solution provided can enable a better understanding of the content. The hypothesis that guided the planning of activities was that the scientific content studied throughout its history comes closer to the cognitive universe, not only of the student, but of man himself