The Experts below are selected from a list of 114 Experts worldwide ranked by ideXlab platform
Brenda Mccowan - One of the best experts on this subject based on the ideXlab platform.
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a multiplex Centrality Metric for complex social networks sex social status and family structure predict multiplex Centrality in rhesus macaques
PeerJ, 2020Co-Authors: Brianne A Beisner, Niklas Braun, Marton Posfai, Jessica J Vandeleest, Raissa M Dsouza, Brenda MccowanAbstract:Members of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals' health and fitness. Multilayer network approaches, where each interaction type represents a different layer of the social network, have the potential to better capture this complexity than single layer approaches. Calculating individuals' Centrality within a multilayer social network can reveal keystone individuals and more fully characterize social roles. However, existing measures of multilayer Centrality do not account for differences in the dynamics and functionality across interaction layers. Here we validate a new method for quantifying multiplex Centrality called consensus ranking by applying this method to multiple social groups of a well-studied nonhuman primate, the rhesus macaque. Consensus ranking can suitably handle the complexities of animal social life, such as networks with different properties (sparse vs. dense) and biological meanings (competitive vs. affiliative interactions). We examined whether individuals' attributes or socio-demographic factors (sex, age, dominance rank and certainty, matriline size, rearing history) were associated with multiplex Centrality. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups. Consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors. Generalized linear mixed models showed that consensus ranking detected known social patterns in rhesus macaques, showing that multiplex Centrality was greater in high-ranking males with high certainty of rank and females from the largest families. In addition, consensus ranks also showed that females from very small families and mother-reared (compared to nursery-reared) individuals were more central, showing that consideration of multiple social domains revealed individuals whose social Centrality and importance might otherwise have been missed.
Oueis Jad - One of the best experts on this subject based on the ideXlab platform.
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Accès radio et fonctionnalités de base dans les réseaux mobiles auto-déployables
HAL CCSD, 2018Co-Authors: Oueis JadAbstract:Self-deployable mobile networks are a novel family of cellular networks, that can be rapidly deployed, easily installed, and operated on demand, anywhere, anytime. They target diverse use cases and provide network services when the classical network fails, is not suitable, or simply does not exist: when the network saturates during crowded events, when first responders need private broadband communication in disaster-relief and mission-critical situations, or when there is no infrastructure in areas with low population density. These networks are challenging a long-standing vision of cellular networks by eliminating the physical separation between the radio access network (RAN) and the core network (CN). In addition to providing RAN functionalities, such as radio signal processing and radio resource management, a base station can also provide those of the CN, such as session management and routing, in addition to housing application servers. As a result, a base station with no backhaul connection to a traditional CN can provide local services to users in its vicinity. To cover larger areas, several base stations must interconnect. With the CN functions co-located with the RAN, the links interconnecting the BSs form the backhaul network. Being setup by the BSs, potentially in an ad hoc manner, the latter may have a limited bandwidth. In this thesis, we build on the properties distinguishing self-deployable networks to revisit classical RAN problems but in the self-deployable context, and address the novel challenges created by the core network architecture. Starting with the RAN configuration, we propose an algorithm that sets a frequency and power allocation scheme. The latter outperforms conventional frequency reuse schemes in terms of the achieved user throughput and is robust facing variations in the number of users and their distribution in the network. Once the RAN is configured, we move to the CN organization, and address both centralized and distributed CN functions placements. For the centralized placement, building on the shortages of state of the art Metrics, we propose a novel Centrality Metric that places the functions in a way that maximizes the traffic that can be exchanged in the network. For the distributed placement, we evaluate the number of needed instances of the CN functions and their optimal placement, considering the impact on the backhaul bandwidth. We further highlight the advantages of distributing CN functions, from a backhaul point of view. Accordingly, we tackle the user attachment problem to determine the CN instances serving each user when the former are distributed. Finally, with the network ready to operate, and users starting to arrive, we tackle the user association problem. We propose a novel network-aware association policy adapted to self-deployable networks, that outperforms a traditional RAN-based policy. It jointly accounts for the downlink, the uplink, the backhaul and the user throughput request.Les réseaux mobiles auto-déployables sont des réseaux qui peuvent être rapidement déployés, facilement installés, sur demande, n’importe où, et n’importe quand. Ils visent divers cas d’utilisation pour fournir des services aux utilisateurs lorsque le réseau classique ne peut pas être utilisé, ou n’existe pas : lors d’événements publics, lors des situations critiques, ou dans les zones isolées. Ces réseaux font évoluer l’architecture d’un réseau classique, en éliminant la séparation physique qui existe entre le réseau d’accès et le cœur de réseau. Cette séparation est désormais uniquement fonctionnelle, vu qu’une station de base est colocalisée avec les fonctionnalités du réseau de cœur, telles que la gestion de session et le routage, en plus des serveurs d’applications. Une station de base, toute seule, sans connexion à un réseau externe, fournit des services aux utilisateurs dans sa zone de couverture. Lorsque plusieurs stations de base sont interconnectées, les liens entre elles forment un réseau d’interconnexion, qui risque d’avoir une capacité limitée. Dans ce travail, nous nous appuyons sur les propriétés distinguant les réseaux auto-déployables pour revisiter des problèmes classiques du réseau d’accès dans ce nouvel contexte, mais aussi pour aborder de nouveaux défis créés par l’architecture du réseau. Tout d’abord, nous proposons un algorithme qui retourne un schéma d’allocation de fréquences et de puissances pour les stations de base. Celui-ci augmente considérablement les débits des utilisateurs par rapport aux schémas classiques de réutilisation de fréquences. Ensuite, nous traitons le problème de placement des fonctionnalités du cœur du réseau. Pour le placement centralisé, nous proposons une nouvelle métrique de centralité qui permet de placer les fonctions de façon à maximiser le trafic pouvant être échangé dans le réseau. Pour le placement distribué, nous évaluons le nombre de fonctions nécessaires et leur placement optimal, en tenant compte de l’impact sur la capacité du réseau d’interconnexion. Nous démontrons aussi les avantages du placement distribué par rapport au centralisé en terme de consommation de ressources sur le réseau d’interconnexion. Dans le même contexte, nous abordons le problème d’attachement des utilisateurs, lorsque les fonctionnalités du cœur de réseau sont distribuées, pour déterminer par laquelle de ces fonctionnalités un utilisateur est-il servi. Enfin, avec le réseau d’accès configuré et le cœur de réseau organisé, les utilisateurs commencent à arriver. Alors, nous abordons le problème de l’association des utilisateurs. Nous proposons une nouvelle politique d’association adaptée aux propriétés des réseaux auto-déployables. Cette politique réduit la probabilité de blocage par rapport aux politiques classiques basées uniquement sur la qualité de la voie descendante, en tenant compte à la fois des ressources du réseau d’accès, des ressources sur le réseau d’interconnexion, et des demandes des utilisateurs
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Accès radio et fonctionnalités cœurs dans les réseaux mobiles auto-déployables
HAL CCSD, 2018Co-Authors: Oueis JadAbstract:Self-deployable mobile networks are a novel family of cellular networks, that can be rapidly deployed, easily installed, and operated on demand, anywhere, anytime. They target diverse use cases and provide network services when the classical network fails, is not suitable, or simply does not exist: for example, when the network saturates during crowded events, when first responders need private broadband communication in disaster-relief and mission-critical situations, or when there is no infrastructure in areas with low population density. These networks are challenging a long-standing vision of cellular networks. Indeed, classical cellular networks are the result of careful planning and deployment strategies. Their fixed and hierarchical architecture is based on a clear physical separation between the radio access network (RAN) and the core network (CN), with an over-provisioned backhaul between them. On the contrary, the rapid deployment nature of self-deployable networks short-circuits the thorough planning phase. The network needs to self-configure and self-organize. Moreover, the split between the RAN and the CN is only functional. In fact, in addition to providing typical RAN functionalities, such as radio signal processing and radio resource management, a base station can also provide those of the CN, such as session management, routing, and authentication, in addition to housing application servers, based on virtualization technologies. As a result, a base station with no backhaul connection to a traditional CN is capable of providing local services to users in its vicinity. To cover larger areas, several base stations must interconnect. With the CN functions co-located with the RAN, the links interconnecting the BSs form the backhaul network. Being setup by the BSs, potentially in an ad hoc manner, the latter may have a limited bandwidth.In this thesis, we build on the properties distinguishing self-deployable networks to revisit classical RAN problems but in the self-deployable context, and address the novel challenges created by the core network architecture. Starting with the RAN configuration, we propose an algorithm that sets a frequency and power allocation scheme. The latter outperforms conventional frequency reuse schemes in terms of the achieved user throughput, and is robust facing variations in the number of users and their distribution in the network. Once the RAN is configured, we move to the CN organization, and address both centralized and distributed CN functions placements. For the centralized placement, building on the shortages of state of the art Metrics, we propose a novel Centrality Metric that places the functions in a way that maximizes the traffic that can be exchanged in the network. For the distributed placement, we evaluate the number of needed instances of the CN functions and their optimal placement, taking into account the impact on the backhaul bandwidth. We further highlight the advantages of distributing CN functions, from a backhaul point of view.Accordingly, we tackle the user attachment problem to determine the CN instances serving each user when the former are distributed. Finally, with the network ready to operate, and users starting to arrive, we tackle the user association problem. We propose a novel network-aware association policy adapted to the self-deployable network attributes, that outperforms a traditional RAN-based policy. It jointly accounts for the downlink, the uplink, the backhaul and the user throughput request, and mitigates both RAN and backhaul bottlenecks.Les réseaux mobiles auto-déployables sont des réseaux qui peuvent être rapidement déployés, facilement installés, sur demande, n'importe où, et n'importe quand. Ils visent divers cas d'utilisation pour fournir des services aux utilisateurs lorsque le réseau classique ne peut pas être utilisé, ou n'existe pas : par exemple, lorsque le réseau est saturé lors d'événements publics, lorsque les services de secours ont besoin d’un réseau qui leur est dédié dans les situations critiques, ou lorsqu’on a besoin de couverture dans les zones isolées.Ces réseaux font évoluer l’architecture d’un réseau classique, en éliminant la séparation physique qui existe entre le réseau d’accès et le cœur de réseau. La séparation entre les deux est désormais uniquement fonctionnelle, vu qu’une station de base est colocalisée avec les fonctionnalités traditionnelles du réseau de cœur, telles que la gestion de session et le routage, en plus des serveurs d’applications, à travers la virtualisation de ces derniers. Une station de base, toute seule, sans connexion à un réseau de cœur externe, est capable de fournir des services aux utilisateurs dans sa zone de couverture. Lorsque plusieurs stations de base sont interconnectées, les liens entre elles forment un réseau d'interconnexion, qui risque d’avoir une capacité limitée. Dans ce travail, nous nous appuyons sur les propriétés qui distinguent les réseaux mobiles auto-déployables pour revisiter des problèmes classiques du réseau d’accès dans ce nouvel contexte, mais aussi pour aborder de nouveaux défis créés par l'architecture du réseau de cœur et du réseau d’interconnexion. Tout d’abord, pour la configuration du réseau d’accès, nous proposons un algorithme qui retourne un schéma d’allocation de fréquences et de puissances pour les stations de base. Notre proposition augmente considérablement les débits des utilisateurs en comparaison avec des schémas classiques de réutilisation de fréquences. Ensuite, nous nous intéressons à l'organisation du cœur de réseau. Nous traitons le problème de placement des fonctionnalités de ce dernier, qu’elles soient centralisées ou distribuées. Pour le placement centralisé, nous proposons une nouvelle métrique de centralité qui permet de placer les fonctions de façon à maximiser le trafic pouvant être échangé dans le réseau. Pour le placement distribué, nous évaluons le nombre de fonctions nécessaires et leur placement optimal, en tenant compte de l'impact sur la capacité du réseau d’interconnexion entre les stations de base. En outre, nous démontrons les avantages d’un placement distribué par rapport à un placement centralisé en terme de consommation de ressources sur le réseau d’interconnexion. Dans le même contexte, nous abordons le problème d’attachement des utilisateurs, lorsque les fonctionnalités du cœur de réseau sont distribuées, pour déterminer par laquelle de ces fonctionnalités un utilisateur est-il servi. Enfin, avec le réseau d’accès configuré et le cœur de réseau organisé, les utilisateurs commencent à arriver. Alors, nous abordons le problème de l'association des utilisateurs. Nous proposons une nouvelle politique d'association adaptée aux propriétés des réseaux auto-déployables. Cette politique réduit la probabilité de blocage par rapport aux politiques classiques basées uniquement sur la qualité de la voie descendante, en tenant compte à la fois des ressources du réseau d’accès, des ressources sur le réseau d’interconnexion, et des demandes des utilisateurs en terme de débit
Brianne A Beisner - One of the best experts on this subject based on the ideXlab platform.
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a multiplex Centrality Metric for complex social networks sex social status and family structure predict multiplex Centrality in rhesus macaques
PeerJ, 2020Co-Authors: Brianne A Beisner, Niklas Braun, Marton Posfai, Jessica J Vandeleest, Raissa M Dsouza, Brenda MccowanAbstract:Members of a society interact using a variety of social behaviors, giving rise to a multi-faceted and complex social life. For the study of animal behavior, quantifying this complexity is critical for understanding the impact of social life on animals' health and fitness. Multilayer network approaches, where each interaction type represents a different layer of the social network, have the potential to better capture this complexity than single layer approaches. Calculating individuals' Centrality within a multilayer social network can reveal keystone individuals and more fully characterize social roles. However, existing measures of multilayer Centrality do not account for differences in the dynamics and functionality across interaction layers. Here we validate a new method for quantifying multiplex Centrality called consensus ranking by applying this method to multiple social groups of a well-studied nonhuman primate, the rhesus macaque. Consensus ranking can suitably handle the complexities of animal social life, such as networks with different properties (sparse vs. dense) and biological meanings (competitive vs. affiliative interactions). We examined whether individuals' attributes or socio-demographic factors (sex, age, dominance rank and certainty, matriline size, rearing history) were associated with multiplex Centrality. Social networks were constructed for five interaction layers (i.e., aggression, status signaling, conflict policing, grooming and huddling) for seven social groups. Consensus ranks were calculated across these five layers and analyzed with respect to individual attributes and socio-demographic factors. Generalized linear mixed models showed that consensus ranking detected known social patterns in rhesus macaques, showing that multiplex Centrality was greater in high-ranking males with high certainty of rank and females from the largest families. In addition, consensus ranks also showed that females from very small families and mother-reared (compared to nursery-reared) individuals were more central, showing that consideration of multiple social domains revealed individuals whose social Centrality and importance might otherwise have been missed.
Kristina Lerman - One of the best experts on this subject based on the ideXlab platform.
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parameterized Centrality Metric for network analysis
Physical Review E, 2011Co-Authors: Rumi Ghosh, Kristina LermanAbstract:A variety of Metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-Centrality [P. Bonacich, Am. J. Sociol. 92, 1170 (1987)], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this Metric and use it to study network structure, for example, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method for community detection to use this Metric as the measure of node connectivity. Normalized alpha-Centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. Studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed Metric to several benchmark networks and show that it leads to better insights into network structure than alternative Metrics.
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Centrality Metric for dynamic networks
arXiv: Computers and Society, 2010Co-Authors: Kristina Lerman, Rumi Ghosh, Jeonhyung KangAbstract:Centrality is an important notion in network analysis and is used to measure the degree to which network structure contributes to the importance of a node in a network. While many different Centrality measures exist, most of them apply to static networks. Most networks, on the other hand, are dynamic in nature, evolving over time through the addition or deletion of nodes and edges. A popular approach to analyzing such networks represents them by a static network that aggregates all edges observed over some time period. This approach, however, under or overestimates Centrality of some nodes. We address this problem by introducing a novel Centrality Metric for dynamic network analysis. This Metric exploits an intuition that in order for one node in a dynamic network to influence another over some period of time, there must exist a path that connects the source and destination nodes through intermediaries at different times. We demonstrate on an example network that the proposed Metric leads to a very different ranking than analysis of an equivalent static network. We use dynamic Centrality to study a dynamic citations network and contrast results to those reached by static network analysis.
Stuart R Borrett - One of the best experts on this subject based on the ideXlab platform.
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evaluating control of nutrient flow in an estuarine nitrogen cycle through comparative network analysis
Ecological Engineering, 2016Co-Authors: David E Hines, Stuart R Borrett, Pawandeep SinghAbstract:Abstract Ecologists, ecosystem managers and ecological engineers often seek to identify which components of an ecosystem are most important to its functioning. Ecosystem Network Analyses (ENA) can be used as a tool to address this challenge while taking into consideration the complex direct and indirect interactions that occur in natural systems. One way that ENA can inform researchers and policy makers is through a broad array of Centrality Metrics, which quantitatively describe the relative importance of each ecosystem component. Control analysis, a type of ENA, identifies which ecosystem members regulate the organization and distribution of energy matter once it enters the ecosystem. We applied two subroutines of control analysis, system control and control difference, to two nitrogen cycling models constructed at sites with different salinity regimes (one oligohaline and one polyhaline) in the Cape Fear River Estuary, NC, USA. We compared the analysis results for these two models to infer how salinity and seawater intrusion might change the control relationships, and therefore functional importance, of nitrogen cycling components. We assert that system control analysis can be used as a Centrality Metric for evaluating the relative function of ecosystem components, and we compared the system control results to three Centrality measures that are established in the literature. Spearmans’ ρ tests for correlation indicated no significant relationship between the system control results and selected Centrality measures, highlighting the ability of this tool to provide novel information. The system control results indicated that sedimentary nitrate and nitrite were most important for regulating the distribution of nitrogen at both sites, highlighting the Centrality of nitrate and nitrite in estuarine nitrogen cycling. However, the control difference analysis, which has finer resolution than system control, indicated that the ammonium pool regulated the movement of nitrogen through the nitrate and nitrite pools at the oligohaline site, while the opposite was observed at the polyhaline site. This reversal of control relationship suggests that seawater intrusion may alter which ecosystem components regulate the distribution of energy matter for reactive nitrogen species in estuaries. This work identifies the utility and uniqueness of system control as a Centrality measure, provides an example of an application of control analysis to identify key ecosystem components, and identifies a potentially important difference in the roles of nitrogen cycling components at two sites.