1,720,966 research outputs found
Collaborative Service Discovery in Mobile Social Networks
Full text linkMobile social networking is a recent paradigm arisen from the wide spread of mobile and wearable devices. Based on the short-range communication interfaces of these devices it is possible to establish opportunistic communications among them and build networks independent to the global one. Challenges introduced by this new type of networks are related to the sharing of resources and services and to the exploitation of the communication opportunities among devices. Limit of existing algorithms, that have sought to fill these shortages, is the lack of attention on the main actor of this service-oriented chain, the user. To this purpose, we introduce the COllaborative seRvice DIscovery ALgorithm (CORDIAL) that leverages both mobility and sociality of the users. We evaluate the performance of CORDIAL combined with different routing protocols for opportunistic networks, and we compare it with a benchmark algorithm (S-Flood) based on flooding and another service discovery algorithm designed to leverage mobile social network features, namely, ServIce DiscovEry in Mobile sociAl Networks (SIDEMAN). Our results show that the performance of CORDIAL remains stable with the different routing algorithms and that, in function of the query forwarding strategy triggered, CORDIAL matches the performance of S-Flood in terms of Query Response Time, achieving a better proactivity score with respect S-Flood and SIDEMAN as well
Enhancing Mobile Edge Computing Architecture with Human-driven Edge Computing Model
No full textIn an increasingly interconnected world, mobile and wearable devices, through short range communication interfaces and sensors, become needful tools for collecting and disseminating information in high population density environments. In this context MCS, leveraging people’s roaming and their devices’ resources, raised the citizen from mere walk-on part to active participant in the knowledge building and data dissemination process. At the same time, MEC architecture has recently enhanced the two-layer cloud-device architectural model easing the exchange of information and shifting most computational cost from devices towards middle-layer proxies, namely, network edges. We introduce Human-driven Edge Computing, a new model which melts together the power of MEC platform and the large-scale sensing of MCS in order to realize a better data spreading and environmental coverage in smart cities. In addition, will be briefly discussed the main sociological aspects related to human behavior and how they can actually influence the exchange of data in large-scale sensor networks
A Social-Based Approach to Mobile Edge Computing
No full textMobile Edge Computing (MEC) opens to the opportunity of moving high-volumes of data from the cloud to locations where the information is actually accessed. In turn, the combination of MEC with the Mobile Crowdsensing approach, using a restricted number of devices with respect the number of base stations, matches the performance of the conventional MEC middleware layer ensuring the same spatial coverage. In this work, we envision a MEC architecture composed by mobile and fixed edges. Their goal is to optimize the share of contents among users by exploiting their mobility and sociality. We first present an algorithm to identify a suitable set of mobile edges and we show how such selection increases the performance of a content-sharing scenario. Our experiments are based on the ParticipAct dataset, which captures the mobility of about 170 users for 10 months. The experiments show that the number of requests that can be served mobile edges is similar to that of requests served by fixed edges, and then that mobile edges can be considered a viable (and lowcost) alternative to fixed edges
Impact of Evolutionary Community Detection Algorithms for Edge Selection Strategies
Full text linkThe combination of the edge computing paradigm with Mobile CrowdSensing (MCS) is a promising approach. However,
the selection of the proper edge nodes is a crucial aspect that greatly affects the performance of the extended architecture. This work studies the performance of an edge-based MCS architecture with ParticipAct, a real-word experimental dataset. We present a community-based edge selection strategy and we measure two key metrics, namely latency and the number of requests satisfied. We show how they vary by adopting three evolutionary community detection algorithms, TILES, Infomap and iLCD configured by changing several configuration settings. We also study the two metrics, by varying the number of edge nodes selected so that to show its benefit
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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