Frontiers of Wireless and Mobile Communications

Raychaudhuri, Dipankar; Mandayam, Narayan B.

doi:10.1109/jproc.2011.2182095

Cited by 185 publications

(102 citation statements)

References 82 publications

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“…Cada nodo configura su participación en la red de forma autónoma, conociendo únicamente la información de los vecinos que se encuentran en su radio de transmisión. Entre sus principales características se encuentran [1], [2]:…”

Section: Características De Las Redes Ad Hocunclassified

Caracterización de un clúster y sus recursos en una red Ad Hoc a partir de la distribución geométrica truncada

Ospina-López¹,

Ortiz-Triviñio²

2015

Iteckne

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Resumen-Una de las propiedades esperadas en las redes ad hoc es la capacidad de aumentar su tamaño recibiendo nuevos nodos y configurando nuevas aplicaciones sin afectar la calidad de los servicios ofrecidos. Esta propiedad, llamada escalabilidad se ve afectada por la naturaleza descentralizada de las redes ad hoc y hace necesario desarrollar mecanismos que le permitan a un gran número de nodos trabajar de manera conjunta sin afectar el rendimiento de la red. En este trabajo, proponemos un modelo estocástico basado en la distribución geométrica truncada, el cual permite caracterizar el nivel de recursos en una arquitectura jerárquica, para luego establecer una relación adecuada entre el nivel de recursos de dos capas sucesivas de la red.Palabras clave-Redes Ad Hoc, Escalabilidad, Modelo Estocástico, Distribución Geométrica, Arquitectura de red.Abstract: One of the expected properties of the ad hoc networks is the ability to increase its size to receive new nodes and configure new applications without affecting the quality of services. This property, called scalability is affected by the decentralized nature of ad hoc networks making it necessary to develop mechanisms that allow a large number of nodes work together without affecting network performance. In this paper, we propose a stochastic model based on the geometric distribution, which allows to characterize the level of resources in a hierarchical architecture and then establish an appropriate relationship between the level of resources of two successive layers of the network.Keywords-Ad hoc Networks, Scalability, Stochastic Model, Geometric Distribution, Network Architecture. INTRODUCCIÓNLas redes ad hoc son un paradigma totalmente distinto a las redes tradicionales, carecen por completo de una infraestructura fija, dan completa autonomía a los nodos para configurar su participación en la red. Esta naturaleza descentralizada trae consigo la aparición de propiedades emergentes y genera la necesidad de incorporar en los nodos ciertas características que les permitan configurarse e integrarse como parte de la red sin afectar su rendimiento.Una de las propiedades esperadas en las redes ad hoc es la capacidad de aumentar de tamaño al recibir nuevos nodos y configurar nuevas aplicaciones sin afectar la calidad en los servicios ofrecidos. Esta propiedad denominada escalabilidad, es uno de los principales desafíos en el diseño de protocolos y una característica fundamental para lograr redes ad hoc con una alta capacidad de despliegue. En el siguiente artículo se propone un modelo basado en la distribución geométrica truncada, el cual permite caracterizar los recursos de una red bajo una arquitectura jerárquica y, posteriormente, establecer una función que permita obtener la relación adecuada entre el nivel de recursos de dos capas sucesivas de la red.El artículo está organizado de la siguiente forma: primero, se hizo una breve revisión sobre las principales características de las redes ad hoc;Caracterización de un clúster y sus recursos en una red Ad Hoc a partir ...

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Section: Características De Las Redes Ad Hocunclassified

Caracterización de un clúster y sus recursos en una red Ad Hoc a partir de la distribución geométrica truncada

Ospina-López¹,

Ortiz-Triviñio²

2015

Iteckne

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“…In addition to advances in cooperative spectrum sensing, CR itself is evolving to support greater data transmission capacity [4] and more flexibility [5] to coexist with other techniques. Especially, recent developments in spectrum regulatory rules, i.e.…”

Section: A Advances In Cr and Cooperative Spectrum Sensingmentioning

confidence: 99%

Energy-Efficient Cooperative Sensing Scheduling for Multi-Band Cognitive Radio Networks

Sun¹,

Tsang

2013

IEEE Trans. Wireless Commun.

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Abstract-In this paper, by taking both sensing performance and energy efficiency into consideration, the Cooperative Sensing Scheduling (CSS) problem for multi-band Cognitive Radio Networks (CRNs) is investigated under a practical scenario where both Primary User (PU) channels and Secondary Users (SUs) have heterogeneous characteristics. Unlike many existing works that merely claim that the CSS problem is NP-hard and then turn to heuristic methods, we analyze this problem under a solid discrete-convex framework. After formulating the CSS problem as a nonlinear binary programming problem, we adopt a threestep approach to solve it. In the first step, the number of SUs assigned to sense each PU channel is determined with the M/M ♮ -convex theory. Based on the results obtained in the first step, we then find the SU assignment using the L/L ♮ -convex theory in the second step. In the last step, the optimal number of SUs participating in sensing is obtained based on the SU assignment obtained in step two. By combining these three steps, a complete and efficient SU assignment scheme is obtained. Numerical results are provided to evaluate the performance of our proposed SU assignment scheme and validate the theoretical analysis.

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“…The architecture for the mobile network is based on the evolved UMTS Terrestrial Radio Access Network (e-UTRAN) (3GGPP, 2012;Dahlman et al, 2006). In the case of LTE, it has been assumed that major changes with significant impact will not happen in the current cellular commercial architecture within the time period considered in this paper (up to 2020) in spite of promising proposals on mesh networks and software-defined radio (Raychaudhuri & Mandayam, 2012).…”

Section: Network Architecture and Active Devicesmentioning

confidence: 99%

How much energy will your NGN consume? A model for energy consumption in next generation access networks: The case of Spain

Coomonte¹,

Feijóo²,

Ramos³

et al. 2013

Telecommunications Policy

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The contribution to global energy consumption of the information and communications technology (ICT) sector has increased considerably in the last decade, along with its growing relevance to the overall economy. This trend will continue due to the seemingly ever greater use of these technologies, with broadband data traffic generated by the usage of telecommunication networks as a primary component. In fact, in response to user demand, the telecommunications industry is initiating the deployment of next generation networks (NGNs). However, energy consumption is mostly absent from the debate on these deployments, in spite of the potential impact on both expenses and sustainability.[n addition, consumers are unaware of the energy impact of their choices in ultra-broadband services. This paper focuses on forecasting energy consumption in the access part of NGNs by modelling the combined effect of the deployment of two different ultra-broadband technologies (FTTH-GPON and LTE), the evolution of traffic per user, and the energy consumption in each of the networks and user devices. Conclusions are presented on the levels of energy consumption, their cost and the impact of different network design parameters. The effect of technological developments, techno-economic and policy decisions on energy consumption is highlighted. On the consumer side, practical figures and comparisons across technologies are provided. Although the paper focuses on Spain, the analysis can be extended to similar countries.

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Frontiers of Wireless and Mobile Communications

Cited by 185 publications

References 82 publications

Caracterización de un clúster y sus recursos en una red Ad Hoc a partir de la distribución geométrica truncada

Caracterización de un clúster y sus recursos en una red Ad Hoc a partir de la distribución geométrica truncada

Energy-Efficient Cooperative Sensing Scheduling for Multi-Band Cognitive Radio Networks

How much energy will your NGN consume? A model for energy consumption in next generation access networks: The case of Spain

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