Connectivity analysis in clustered wireless sensor networks powered by solar energy

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Emerging 5G communication paradigms, such as machine-type communication, have triggered an explosion in ad-hoc applications that require connectivity among the nodes of wireless networks. Ensuring a reliable network operation under fading conditions is not straightforward, as the transmission schemes and the network topology, i.e., uniform or clustered deployments, affect the performance and should be taken into account. Moreover, as the number of nodes increases, exploiting natural energy sources and wireless energy harvesting (WEH) could be the key to the elimination of maintenance costs while also boosting immensely the network lifetime. In this way, zero-energy wireless-powered sensor networks (WPSNs) could be achieved, if all components are powered by green sources. Hence, designing accurate mathematical models that capture the network behavior under these circumstances is necessary to provide a deeper comprehension of such networks. In this paper, we provide an analytical model for the connectivity in a large-scale zero-energy clustered WPSN under two common transmission schemes, namely, unicast and broadcast. The sensors are WEH-enabled, while the network components are solar-powered and employ a novel energy allocation algorithm. In our results, we evaluate the tradeoffs among the various scenarios via extensive simulations and identify the conditions that yield a fully connected zero-energy WPSN.Peer ReviewedPostprint (author's final draft

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Dual-battery empowered green cellular networks

With awareness of the potential harmful effects to the environment and climate change, on-grid brown energy consumption of information and communications technology (ICT) has drawn much attention. Cellular base stations (BSs) are among the major energy guzzlers in ICT, and their contributions to the global carbon emissions increase sustainedly. It is essential to leverage green energy to power BSs to reduce their on-grid brown energy consumption. However, in order to furthest save on-grid brown energy and decrease the on-grid brown energy electricity expenses, most existing green energy related works only pursue to maximize the green energy utilization while compromising the services received by the mobile users. In reality, dissatisfaction of services may eventually lead to loss of market shares and profits of the network providers. In this research, a dual-battery enabled profit driven user association scheme is introduced to jointly consider the traffic delivery latency and green energy utilization to maximize the profits for the network providers in heterogeneous cellular networks. Since this profit driven user association optimization problem is NP-hard, some heuristics are presented to solve the problem with low computational complexity. Finally, the performance of the proposed algorithm is validated through extensive simulations. In addition, the Internet of Things (IoT) heralds a vision of future Internet where all physical things/devices are connected via a network to promote a heightened level of awareness about our world and dramatically improve our daily lives. Nonetheless, most wireless technologies utilizing unlicensed bands cannot provision ubiquitous and quality IoT services. In contrast, cellular networks support large-scale, quality of service guaranteed, and secured communications. However, tremendous proximal communications via local BSs will lead to severe traffic congestion and huge energy consumption in conventional cellular networks. Device-to-device (D2D) communications can potentially offload traffic from and reduce energy consumption of BSs. In order to realize the vision of a truly global IoT, a novel architecture, i.e., overlay-based green relay assisted D2D communications with dual batteries in heterogeneous cellular networks, is introduced. By optimally allocating the network resource, the introduced resource allocation method provisions the IoT services and minimizes the overall energy consumption of the pico relay BSs. By balancing the residual green energy among the pico relay BSs, the green energy utilization is maximized; this furthest saves the on-grid energy. Finally, the performance of the proposed architecture is validated through extensive simulations. Furthermore, the mobile devices serve the important roles in cellular networks and IoT. With the ongoing worldwide development of IoT, an unprecedented number of edge devices imperatively consume a substantial amount of energy. The overall IoT mobile edge devices have been predicted to be the leading energy guzzler in ICT by 2020. Therefore, a three-step green IoT architecture is proposed, i.e., ambient energy harvesting, green energy wireless transfer and green energy balancing, in this research. The latter step reinforces the former one to ensure the availability of green energy. The basic design principles for these three steps are laid out and discussed. In summary, based on the dual-battery architecture, this dissertation research proposes solutions for the three aspects, i.e., green cellular BSs, green D2D communications and green devices, to hopefully and eventually actualize green cellular access networks, as part of the ongoing efforts in greening our society and environment

GreenDelivery: Proactive Content Caching and Push with Energy-Harvesting-based Small Cells

The explosive growth of mobile multimedia traffic calls for scalable wireless access with high quality of service and low energy cost. Motivated by the emerging energy harvesting communications, and the trend of caching multimedia contents at the access edge and user terminals, we propose a paradigm-shift framework, namely GreenDelivery, enabling efficient content delivery with energy harvesting based small cells. To resolve the two-dimensional randomness of energy harvesting and content request arrivals, proactive caching and push are jointly optimized, with respect to the content popularity distribution and battery states. We thus develop a novel way of understanding the interplay between content and energy over time and space. Case studies are provided to show the substantial reduction of macro BS activities, and thus the related energy consumption from the power grid is reduced. Research issues of the proposed GreenDelivery framework are also discussed.Comment: 15 pages, 5 figures, accepted by IEEE Communications Magazin

Network association strategies for an energy harvesting aided super-wifi network relying on measured solar activity

The super-WiFi network concept has been proposed for nationwide Internet access in the United States. However, the traditional mains power supply is not necessarily ubiquitous in this large-scale wireless network. Furthermore, the non-uniform geographic distribution of both the based-stations and the tele-traffic requires carefully considered user association. Relying on the rapidly developing energy harvesting techniques, we focus our attention on the sophisticated access point (AP) selection strategies conceived for the energy harvesting aided super-WiFi network. Explicitly, we propose a solar radiation model relying on the historical solar activity observation data provided by the University of Queensland, followed by a beneficial radiation parameter estimation method. Furthermore, we formulate both a Markov decision process (MDP) as well as a partially observable MDP (POMDP) for supporting the users’ decisions on beneficially selecting APs. Moreover, we conceive iterative algorithms for implementing our MDP and POMDP-based AP-selection, respectively. Finally, our performance results are benchmarked against a range of traditional decision-making algorithms

Network resource allocation policies with energy transfer capabilities

During the last decades, mobile network operators have witnessed an exponential increase in the traffic demand, mainly due to the high request of services from a huge amount of users. The trend is of a further increase in both the traffic demand and the number of connected devices over the next years. The traffic load is expected to have an annual growth rate of 53% for the mobile network alone, and the upcoming industrial era, which will connect different types of devices to the mobile infrastructure including human and machine type communications, will definitely exacerbate such an increasing trend. The current directions anticipate that future mobile networks will be composed of ultra dense deployments of heterogeneous Base Stations (BSs), where BSs using different transmission powers coexist. Accordingly, the traditional Macro BSs layer will be complemented or replaced with multiple overlapping tiers of small BSs (SBSs), which will allow extending the system capacity. However, the massive use of Information and Communication Technology (ICT) and the dense deployment of network elements is going to increase the level of energy consumed by the telecommunication infrastructure and its carbon footprint on the environment. Current estimations indicates that 10% of the worldwide electricity generation is due to the ICT industry and this value is forecasted to reach 51% by 2030, which imply that 23% of the carbon footprint by human activity will be due to ICT. Environmental sustainability is thus a key requirement for designing next generation mobile networks. Recently, the use of Renewable Energy Sources (RESs) for supplying network elements has attracted the attention of the research community, where the interest is driven by the increased efficiency and the reduced costs of energy harvesters and storage devices, specially when installed to supply SBSs. Such a solution has been demonstrated to be environmentally and economically sustainable in both rural and urban areas. However, RESs will entail a higher management complexity. In fact, environmental energy is inherently erratic and intermittent, which may cause a fluctuating energy inflow and produce service outage. A proper control of how the energy is drained and balanced across network elements is therefore necessary for a self-sustainable network design. In this dissertation, we focus on energy harvested through solar panels that is deemed the most appropriate due to the good efficiency of commercial photovoltaic panels as well as the wide availability of the solar source for typical installations. The characteristics of this energy source are analyzed in the first technical part of the dissertation, by considering an approach based on the extraction of features from collected data of solar energy radiation. In the second technical part of the thesis we introduce our proposed scenario. A federation of BSs together with the distributed harvesters and storage devices at the SBS sites form a micro-grid, whose operations are managed by an energy management system in charge of controlling the intermittent and erratic energy budget from the RESs. We consider load control (i.e., enabling sleep mode in the SBSs) as a method to properly manage energy inflow and spending, based on the traffic demand. Moreover, in the third technical part, we introduce the possibility of improving the network energy efficiency by sharing the exceeding energy that may be available at some BS sites within the micro-grid. Finally, a centralized controller based on supervised and reinforcement learning is proposed in the last technical part of the dissertation. The controller is in charge of opportunistically operating the network to achieve efficient utilization of the harvested energy and prevent SBSs blackout.Durante las últimas décadas, los operadores de redes móviles han sido testigos de un aumento exponencial en la demanda de tráfico, principalmente debido a la gran solicitud de servicios de una gran cantidad de usuarios. La tendencia es un aumento adicional tanto en la demanda de tráfico como en la cantidad de dispositivos conectados en los próximos años. Se espera que la carga de tráfico tenga una tasa de crecimiento anual del 53% solo para la red móvil, y la próxima era industrial, que conectará diferentes tipos de dispositivos a la infraestructura móvil, definitivamente exacerbará tal aumento. Las instrucciones actuales anticipan que las redes móviles futuras estarán compuestas por despliegues ultra densos de estaciones base (BS) heterogéneas. En consecuencia, la capa tradicional de Macro BS se complementará o reemplazará con múltiples niveles superpuestos de pequeños BS (SBS), lo que permitirá ampliar la capacidad del sistema. Sin embargo, el uso masivo de la Tecnología de la Información y la Comunicación (TIC) y el despliegue denso de los elementos de la red aumentará el nivel de energía consumida por la infraestructura de telecomunicaciones y su huella de carbono en el medio ambiente. Las estimaciones actuales indican que el 10% de la generación mundial de electricidad se debe a la industria de las TIC y se prevé que este valor alcance el 51% para 2030, lo que implica que el 23% de la huella de carbono por actividad humana se deberá a las TIC. La sostenibilidad ambiental es, por lo tanto, un requisito clave para diseñar redes móviles de próxima generación. Recientemente, el uso de fuentes de energía renovables (RES) para suministrar elementos de red ha atraído la atención de la comunidad investigadora, donde el interés se ve impulsado por el aumento de la eficiencia y la reducción de los costos de los recolectores y dispositivos de almacenamiento de energía, especialmente cuando se instalan para suministrar SBS. Se ha demostrado que dicha solución es ambiental y económicamente sostenible tanto en áreas rurales como urbanas. Sin embargo, las RES conllevarán una mayor complejidad de gestión. De hecho, la energía ambiental es inherentemente errática e intermitente, lo que puede causar una entrada de energía fluctuante y producir una interrupción del servicio. Por lo tanto, es necesario un control adecuado de cómo se drena y equilibra la energía entre los elementos de la red para un diseño de red autosostenible. En esta disertación, nos enfocamos en la energía cosechada a través de paneles solares que se considera la más apropiada debido a la buena eficiencia de los paneles fotovoltaicos comerciales, así como a la amplia disponibilidad de la fuente solar para instalaciones típicas. Las características de esta fuente de energía se analizan en la primera parte técnica de la disertación, al considerar un enfoque basado en la extracción de características de los datos recopilados de radiación de energía solar. En la segunda parte técnica de la tesis presentamos nuestro escenario propuesto. Una federación de BS junto con los cosechadores distribuidos y los dispositivos de almacenamiento forman una microrred, cuyas operaciones son administradas por un sistema de administración de energía a cargo de controlar el presupuesto de energía intermitente y errático de las RES. Consideramos el control de carga como un método para administrar adecuadamente la entrada y el gasto de energía, en función de la demanda de tráfico. Además, en la tercera parte técnica, presentamos la posibilidad de mejorar la eficiencia energética de la red al compartir la energía excedente que puede estar disponible en algunos sitios dentro de la microrred. Finalmente, se propone un controlador centralizado basado en aprendizaje supervisado y de refuerzo en la última parte técnica de la disertación. El controlador está a cargo de operar la red para lograr una utilización eficiente de energía y previene el apagón de SB

Renewables powered cellular networks: Energy field modeling and network coverage

Powering radio access networks using renewables, such as wind and solar power, promises dramatic reduction in the network operation cost and the network carbon footprints. However, the spatial variation of the energy field can lead to fluctuations in power supplied to the network and thereby affects its coverage. This warrants research on quantifying the aforementioned negative effect and designing countermeasure techniques, motivating the current work. First, a novel energy field model is presented, in which fixed maximum energy intensity γ occurs at Poisson distributed locations, called energy centers. The intensities fall off from the centers following an exponential decay function of squared distance and the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. The product between the energy center density and the exponential rate of the decay function, denoted as ψ, is shown to determine the energy field distribution. Next, the paper considers a cellular downlink network powered by harvesting energy from the energy field and analyzes its network coverage. For the case of harvesters deployed at the same sites as base stations (BSs), as γ increases, the mobile outage probability is shown to scale as (cγ-πψ+p), where p is the outage probability corresponding to a flat energy field and $c$ is a constant. Subsequently, a simple scheme is proposed for counteracting the energy randomness by spatial averaging. Specifically, distributed harvesters are deployed in clusters and the generated energy from the same cluster is aggregated and then redistributed to BSs. As the cluster size increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS. Several additional issues are investigated in this paper, including regulation of the power transmission loss in energy aggregation and extensions of the energy field model. © 2002-2012 IEEE.published_or_final_versio

Risco do cultivo de campo de pepino decapado causado por condições desfavoráveis de duração de brilho solar

Solar energy, accessible to plants during sunshine from the sunrise to the sunset is of key importance in productivity of agrocenoses. The aim of the work was to determine risk of pickling cucumber cultivation caused by an unfavorable course of sunshine duration in Poland on the basis of a 40-year research period 1966-2005. The research into the subject was undertaken due to frequent occurrence of sunshine deficiency in Poland and its high temporal and spatial variability. Effect of solar conditions described by sunshine duration in the five development stages on the quantity of the total and marketable yield of cucumber with consideration of a linear trend of an independent variable was determined by means of multiple regression analysis. The accuracy of the equations was evaluated on the basis of, among other things, determination coefficient, average relative forecast error and the indexes: mean bias error (MBE), mean absolute bias error (MABE) and root mean square error (RMSE). Cucumber (Cucumis sativus L.) yield was confirmed for the period from the end of emergence to the beginning of flowering and from the beginning of harvesting to the end of harvesting. Cucumber yield was lower by 18% than the multiannual average in the years 1966-2005 every 1.5-2 years -in the case of the occurrence of the shortage in the period from the end of emergence to the beginning of flowering and by 12-15% every 2-3 years in the period from the beginning of harvesting to the end of harvesting. In four years, out of the 40 considered ones, simultaneously in both cucumber development stages, unfavorable solar conditions occurred, causing reduction by at least 5% in the total yield of the plant in Poland, and in three years - the marketable yield.A disponibilidade de energia solar para as plantas desde o nascer ao por do sol é de fundamental importância para todo agronegócio. O objetivo deste trabalho foi determinar o risco da produção de pepino (Cucumis sativus L.) decapado causado pelo curso desfavorável de duração da radiação solar na Polônia, baseado em um período de 40 anos de pesquisa (1966-2005). A pesquisa foi realizada pelo fato da ocorrência frequente de deficiência de insolação na Polônia e sua alta variabilidade temporal e espacial. O efeito das condições solares descritas pela duração da insolação foi estudado em relação às produtividades total e comerciável de pepino, considerando uma tendência linear de uma variável independente. A precisão das equações foi avaliada com base no coeficiente de determinação, erro médio relativo de precisão e índices: erro médio de bias, erro médio absoluto de bias e raiz do erro médio quadrado. A produtividade foi analisada a partir da emergência até o início do florescimento e do inicio ao fim da colheita. A produtividade de pepino foi 18% menor em relação a media multianual dos anos 1966-2005 cada 1,5-2 anos - nos casos de falta de insolação no período emergência-florescimento e 12-15% menor a cada 2-3 anos na colheita. Com exceção de quarto dentro dos 40 anos estudados, houve condições desfavoráveis de insolação em ambos os estádios estudados, causando uma redução de no mínimo de 5% da produção total da planta na Polônia e, excetos três anos - da produção comercial

Renewable Powered Cellular Networks: Energy Field Modeling and Network Coverage

Powering radio access networks using renewables, such as wind and solar power, promises dramatic reduction in the network operation cost and the network carbon footprints. However, the spatial variation of the energy field can lead to fluctuations in power supplied to the network and thereby affects its coverage. This warrants research on quantifying the aforementioned negative effect and countermeasure techniques, motivating the current work. First, a novel energy field model is presented, in which fixed maximum energy intensity $\gamma$ occurs at Poisson distributed locations, called energy centers. The intensities fall off from the centers following an exponential decay function of squared distance and the energy intensity at an arbitrary location is given by the decayed intensity from the nearest energy center. The product between the energy center density and the exponential rate of the decay function, denoted as $\psi$, is shown to determine the energy field distribution. Next, the paper considers a cellular downlink network powered by harvesting energy from the energy field and analyzes its network coverage. For the case of harvesters deployed at the same sites as base stations (BSs), as $\gamma$ increases, the mobile outage probability is shown to scale as $(c \gamma^{-\pi\psi}+p)$, where $p$ is the outage probability corresponding to a flat energy field and $c$ a constant. Subsequently, a simple scheme is proposed for counteracting the energy randomness by spatial averaging. Specifically, distributed harvesters are deployed in clusters and the generated energy from the same cluster is aggregated and then redistributed to BSs. As the cluster size increases, the power supplied to each BS is shown to converge to a constant proportional to the number of harvesters per BS.Comment: double-column, 13 pages; to appear in IEEE Transactions on Wireless Communication