992 resultados para Cooperative Strategies
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El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.
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Includes bibliographical references (p. [14]-16).
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The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense.
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Relay selection has been considered as an effective method to improve the performance of cooperative communication. However, the Channel State Information (CSI) used in relay selection can be outdated, yielding severe performance degradation of cooperative communication systems. In this paper, we investigate the relay selection under outdated CSI in a Decode-and-Forward (DF) cooperative system to improve its outage performance. We formulize an optimization problem, where the set of relays that forwards data is optimized to minimize the probability of outage conditioned on the outdated CSI of all the decodable relays’ links. We then propose a novel multiple-relay selection strategy based on the solution of the optimization problem. Simulation results show that the proposed relay selection strategy achieves large improvement of outage performance compared with the existing relay selection strategies combating outdated CSI given in the literature.
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The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L.^ Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (n$\sb1$ = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (n$\sb2$ = 19) (at the beginning and end of the term).^ Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge. ^
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The focus of this study was to explain the extent to which theoretically effective teaching strategies taught in a course on generic instructional strategies are being implemented by teachers in their actual teaching practice. ^ A multivariate causal-comparative (ex-post-facto) design was used to answer the research question. A teacher observation protocol, the General Instructional Strategies Analysis (GISA) was constructed and used to assess the utilization of instructional strategies in the classroom. The data of this study also included open-ended field notes taken during observations. ^ Multivariate Analyses of Variance (MANOVA) was used to compare the teaching strategies (set, effective explanation, hands-on activity, cooperative learning activity, higher order questioning, closure) of the group who had taken a general instructional strategies course (N=36) and the group who had not (N=36). Results showed a statistically significant difference between the two groups. The group who had taken the course implemented these strategies more effectively in almost all categories of effective teaching. Follow-up univariate tests of the dependent variables showed significant differences between the two groups in five of the six areas (hands-on activity being an exception). A second MANOVA compared the two groups on the effective use of attending behaviors (teacher movement/eye contact/body language/physical space, brief verbal acknowledgements/voice inflection/modulation/pitch, use of visuals, prompting/probing, praise/feedback/rewards, wait-time I and II). Results also showed a multivariate difference between the two groups. Follow-up univariate tests on the related dependent variables showed that five of the six were significantly different between the two groups. The group who had taken the course implemented the strategies more effectively. An analysis of the field notes provided further evidence regarding the pervasiveness of these differences between the teaching practices of the two groups. ^ It was concluded that taking a course in general instructional strategies increases the utilization of effective strategies in the classroom by teachers. ^
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The hypothesis that the same educational objective, raised as cooperative or collaborative learning in university teaching does not affect students’ perceptions of the learning model, leads this study. It analyses the reflections of two students groups of engineering that shared the same educational goals implemented through two different methodological active learning strategies: Simulation as cooperative learning strategy and Problem-based Learning as a collaborative one. The different number of participants per group (eighty-five and sixty-five, respectively) as well as the use of two active learning strategies, either collaborative or cooperative, did not show differences in the results from a qualitative perspective.
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Abstract: Active or participatory learning by the student within a classroom environment has been fairly recently recognized as an effective, efficient, and superior instructional technique yet few teachers in higher education have adopted this pedagogical strategy. This is especially true in Science where teachers primarily lecture to passively seated students while using static visual aids or multimedia projections. Teachers generally teach as they were taught and lecture formats have been the norm. Although student-learning theories as well as student learning styles, abilities, and understanding strategies have changed, traditional teaching techniques have not evolved past the “chalk and talk” instructional strategy. This research looked into student’s perceptions of cooperative learning or team-based active learning in order to gain insight and some understanding as to how students felt about this learning technique. Student’s attitudes were then compared to student grades to detennine whether cooperative learning impeded or ameliorated academic performance. The results revealed significant differences measured in all the survey questions pertaining to perception or attitudes. As a result of the cooperative learning activities, respondents indicated more agreement to the survey questions pertaining to the benefits of cooperative learning. The experimental group exposed to cooperative learning thus experienced more positive attitudes and perceptions than the groups exposed only to a lecture-based teaching and learning format. Each of the hypotheses tested demonstrated that students had more positive attitudes towards cooperative learning strategies. Recommendations as to future work were presented in order to gain a greater understanding into both student and teacher attitudes towards the cooperative learning model.||Résumé: Lapprentissage actif ou préparatoire par létudiant au sein d’une classe a été reconnu assez récemment comme une technique d’enseignement plus efficace. Cependant, peu d’enseignants ont adopté cette stratégie pedagogique pour l'éducation post-secondaire. Ceci est particulièrement le cas dans le domaine des sciences où les enseignants font surtout usage de cours magistraux avec des étudiants passifs tout en utilisant des aides visuelles statiques ou des projections multimédias. Les professeurs enseignent generalement comme on leur a eux-même enseigné et les cours magistraux ont été la norme par le passé. Les techniques traditionnelles d'enseignernent n'ont pas évolué au-delà de la craie et du tableau noir et ce même si les théories sur l’apprentissage par les étudiants ont changé, tout comme les styles, les habiletés et les stratégies de compréhension d’apprentissage des étudiants. Cette recherche se penche sur les perceptions des étudiants au sujet de l'apprentissage coopératif ou de l'apprentissage actif par équipe de telle sorte qu'on puisse avoir un aperçu et une certaine compréhension de comment les étudiants se sentent par rapport à ces techniques d'apprentissage. Les attitudes des étudiants ont par la suite été comparées aux notes de ceux-ci pour déterminer si l'apprentissage coopératif avait nui ou au contraire amélioré leurs performances académiques. Les résultats obtenus dans l'étude d'ensemble révèlent des différences significatives dans toutes les questions ayant trait à la perception et aux attitudes.
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During the last years tropical forest has been a target of intense study especially due to its recent big scale destruction. Although a lot still needs to be explored, we start realizing how negative can the impact of our actions be for the ecosystem. Subsequently, the living community have been developing strategies to overcome this problem avoiding bottlenecks or even extinctions. Cooperative breeding (CB) has been recently pointed out as one of those strategies. CB is a breeding system where more than two individuals raise one brood. In most of the cases, extra individuals are offspring that delay their dispersal and independent breeding what allows them to help their parents raising their siblings in the subsequent breeding season. Such behavior is believed to be due, per example, to the lack of mates or breeding territories (ecological constraints hypothesis), a consequence of habitat fragmentation and/or disturbance. From this point, CB is easily promoted by a higher reproductive success of group vs pairs or single individuals. Accordingly, during this thesis I explore the early post-fledging survival of a cooperative breeding passerine, namely the impact of individual/habitat quality in its survival probability during the dependence period of the chicks. Our study species is the Cabanis’s greenbul (Phyllastrephus cabanisi), a medium-sized, brownish passerine, classified within the Pycnonotidae family. It is found over part of Central Africa in countries such as Angola, Democratic Republic of the Congo, Mozambique and Kenya, inhabiting primary and secondary forests, as well as woodland of various types up to 2700m of altitude. Previous studies have concluded that PC is a facultative cooperative breeder. This study was conducted in Taita Hills (TH) at the Eastern Arc Mountains (EAM), a chain of mountains running from Southeast Kenya to the South of Tanzania. TH comprises an area of 430 ha and has been suffering intense deforestation reflecting 98% forest reduction over the last 200 years. Nowadays its forest is divided in fragments and our study was based in 5of those fragments. We access the post-fledging survival through radio-telemetry. The juvenile survey was done through the breeding females in which transmitters were placed with a leg-loop technique. Ptilochronology is consider to be the study of feather growth bars and has been used to study the nutritional state of a bird. This technique considers that the feather growth rate is positively proportional to the individual capability of ingesting food and to the food availability. This technique is therefore used to infer for individual/habitat quality. Survival was lowest during the first 5 days post-fledging representing 53.3%. During the next 15 days, risk of predation decreased with only 14.3% more deceased individuals. This represents a total of only 33% survived individuals in the end of the 50 days. Our results showed yet a significant positive relationship between flock size and post-fledging survival as well as between ptilochronology values and post-fledgling survival. In practice, these imply that on this population, as bigger the flock, as greater the post fledging survival and that good habitat quality or good BF quality, will lead to a higher juvenile survival rate. We believe that CB is therefore an adaptive behaviour to the lack of mates/breeding territory originated from the mass forest destruction and disturbance. Such results confirms the critical importance of habitat quality in the post-fledging survival and, for the first time, demonstrates how flock size influences the living probability of the juveniles and therefore how it impacts the (local) population dynamics of this species. In my opinion, future research should be focus in disentangle individual and habitat quality from each other and verify which relationship exist between them. Such study will allow us to understand which factor has a stronger influence in the post-fledging survival and therefore redirect our studies in that direction. In order to confirm the negative impact of human disturbance and forest fragmentation, it would be of major relevance to compare the reproductive strategies and reproductive success of populations living in intact forests and disturbed patches.
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Part 18: Optimization in Collaborative Networks