1,720,994 research outputs found
Energy-Aware Satellite Handover Based on Deep Reinforcement Learning
No full textMultiple Low Earth Orbit (LEO) satellites have been deployed in constellations to provide User Equipments (UE)s with direct Internet connection at all times and from any location. UEs experience several handovers (HO)s during their service period due to the high speed of LEO satellites, which has a bad influence on UEs’ Quality of Service (QoS) if occurred extensively. Furthermore, next-generation communication technologies are intended to serve a broad range of applications each with unique performance needs, thus distinguishing UEs with diverse and varied Traffic-Profiles (TP) has become necessary. Moreover, LEO satellites have limited onboard resources (e.g., energy and channel resources), and the deployed constellations ensure that each UE is covered by more than one LEO satellite at any time, making it difficult to pick the best satellite at each time to provide the best QoS. Therefore, a satellite HO strategy has to effectively use the limited available satellite resources and prevent network congestion while respecting the various TPs per UE. To address the aforementioned challenges, we propose a Load Balancing Energy Aware Satellite Handover (LBEASH) strategy, that is the first in the state of the art to address the limited energy resource of LEO satellites and the variety of UEs’ performance requirements. The proposed LBEASH showcases significant achievements by avoiding unnecessary HOs and achieving a zero blocking rate while balancing the load among the satellites
Reinforcement Learning-Based Load Balancing Satellite Handover Using NS-3
Full text linkThe Fifth-Generation of Mobile Communications (5G) is intended to meet users' growing needs for high-quality services at any time and from any location. The unique features of Low Earth Orbit (LEO) satellites in terms of higher coverage, reliability, and availability, can help expand the reach of 5G and beyond technologies to support those needs. However, because of their high speeds, a single LEO satellite is unable to provide continuous service to multiple User Equipments (UEs) spread over a large (potentially worldwide) area, resulting in the need for LEO satellite constellations with a high number of satellites and a consequent high amount of satellite handovers (HOs). Moreover, UEs can only acquire partial information about the satellite system and compete for the limited available communication resources of the satellites, requiring the implementation of a decentralized satellite HO strategy to avoid network congestion. In this paper, we propose a decentralized Load Balancing Satellite HO (LBSH) strategy based on multi-agent reinforcement Q-learning, implemented within the software Network Simulator 3 (NS-3). LBSH aims to reduce the total number of HOs and the blocking rate while balancing the load distribution among satellites. Our results show that the proposed LBSH method outperforms the state-of-the-art methods in terms of a 95% drop in the average number of HOs per user and an 84% reduction in blocking rate
User Centric Satellite Handover for Multiple Traffic Profiles Using Deep Q-Learning
No full textMultiple Low Earth Orbit (LEO) satellites have recently been launched in constellations to insure direct Internet access to users anywhere and at any time. Due to the high-speed mobility of LEO satellites, users undergo multiple handovers (HO)s during their service time, which has a negative impact on users' Quality of Service (QoS) if occurred in high frequency. Moreover, next-generation communication technologies are designed to support a wide spectrum of applications, including Artificial Intelligence, Virtual Reality, and Internet of Things (IoT). Thus, differentiating User Equipments (UEs) with different and varying Traffic-Profiles (TP) has become necessary due to each application's unique performance requirements. However, LEO satellites have limited onboard resources and the launched constellations ensure that each UE will be covered by more than one LEO satellite at any given moment, making it challenging to select the optimal satellite at any given time to assure the optimum QoS. Therefore, a satellite HO strategy has to effectively use the few available satellite resources and prevent network congestion while respecting the various resource requirements per TP. To address all the above requirements, we propose a user-centric Multi-Agent Deep Q-Network (MADQN) satellite HO strategy, that is the first in the state of the art to address the variety and diversity of UEs' performance requirements and generated traffic statistics. Our method showcases a significant achievement of approximately 60% reduction in HO rate and around 91% reduction in blocking rate compared to conventional single criterion approaches
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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