1,720,961 research outputs found
Dynamic Super Round Based Distributed Task Scheduling for UAV Networks
Full text linkNetworks of Unmanned Aerial Vehicles (UAVs) are emerging in many application domains, e.g., military surveillance. To perform collaborative tasks, the involved UAVs exchange several types of information, e.g., sensor data and commands. The major question here is how to schedule the tasks under dynamic traffic flows to provide network services. Existing solutions use the Round-Robin Strategy (RRS), where the tasks are scheduled statistically by dividing the time into fixed-length rounds. However, the RRS wastes significant network and device resources due to task scheduling in each round. This paper proposes DROVE – a novel clustering approach that allows the UAVs for dynamic task scheduling. However, determining the task scheduling is crucial, as it significantly affects several network parameters, e.g., throughput. Therefore, we devise the problem of distributed task scheduling under dynamic traffic flow scenarios to optimize the throughput. We propose a clustering task scheduling algorithm to serve dynamic traffic flows. Particularly, we integrate the dynamic traffic flows into the Lyapunov drift analysis framework, and determine the throughput optimality of our proposed scheduling algorithm. We perform extensive simulations to validate the effectiveness of DROVE. The results show that DROVE outperforms the state-of-the-art solutions in terms of energy consumption, clustering overhead, throughput, end-to-end delay, flow success rate and packet drop rate. </p
Secure key design approaches using entropy harvesting in wireless sensor network: A survey
Full text linkPhysical layer based security design in wireless sensor networks have gained much importance since the past decade. The various constraints associated with such networks coupled with other factors such as their deployment mainly in remote areas, nature of communication etc. are responsible for development of research works where the focus is secured key generation, extraction, and sharing. Keeping the importance of such works in mind, this survey is undertaken that provides a vivid description of the different mechanisms adopted for securely generating the key as well its randomness extraction and also sharing. This survey work not only concentrates on the more common methods, like received signal strength based but also goes on to describe other uncommon strategies such as accelerometer based. We first discuss the three fundamental steps viz. randomness extraction, key generation and sharing and their importance in physical layer based security design. We then review existing secure key generation, extraction, and sharing mechanisms and also discuss their pros and cons. In addition, we present a comprehensive comparative study of the recent advancements in secure key generation, sharing, and randomness extraction approaches on the basis of adversary, secret bit generation rate, energy efficiency etc. Finally, the survey wraps up with some promising future research directions in this area
Efficient Physical Intrusion Detection in Internet of Things: A Node Deployment Approach
No full textIn Internet of Things (IoT), intrusion detection plays an important role in many applications for detecting malicious intruders. The intruder can be, an unexpected physically moving entity, invading an area under surveillance, or an adversary in a battlefield. Node deployment strategy plays a crucial role in determining the intrusion detection capability of an IoT network. With uniform deployment, the detection probability is the same for any location in the network area. Nevertheless, different applications may need diverse levels of detection probability at key areas within the network. For example, a battlefield surveillance application needs improved detection probability around the headquarter. On the contrary, a Gaussian deployment strategy provides improved detection probability to the key areas due to differentiated node density. However, it is neither energy-efficient nor provides a quick detection of the physical intruder. In this work, we introduce a novel deployment strategy to overcome the above said limitations of both uniform and Gaussian deployments for energy-efficient and quick detection. Initially, we investigate the problem of physical intrusion detection in our introduced deployment strategy considering a realistic sensing model. Furthermore, we examine the effects of different network parameters on the detection probability in details. We also derive the relationship between the different network parameters and connectivity to ensure fast detection. We perform exhaustive experiments on real datasets, primarily, in order to validate the correctness of modeling and analyses. Next, we examine the effects of different network parameters on the detection probability. The results clearly demonstrate that our approach improves the detection probability by more than 25% when compared to two well-known deployment strategies under various network parameters
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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