311 research outputs found

    Design of qos-aware energy-efficient fiber–wireless access networks

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    Energy-efficient network design has recently become a very important topic because of the energy cost increases in service providers’ infrastructures. This is of particular importance in access networks because of the growing demand for digital traffic by end users. Here we address the challenge of reducing the energy consumption of fiber–wireless (FiWi) access networks, that use both optical and radio frequency technologies to provide high bandwidth and ubiquity for end-user applications, while keeping delay under a threshold. Our goal is to find optimal sleep mode schedulings that allow energy consumption to be reduced while keeping packet delay acceptable. For this purpose a mathematical formalization and an algorithm are developed. The results show that the proposed approach is able to reduce the average packet delay, with negligible energy cost increases, in many scenarios, besides being computationally efficient and scalable. The proposed approach may, therefore, serve as a basis for planning and design of quality of service-aware energy-efficient FiWi access networks.This work was supported by FCT (Foundation for Science and Technology) of Portugal within CEOT (Center for Electronic, Optoelectronic and Telecommunications)

    A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

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    Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing

    Research challenges on energy-efficient networking design

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    The networking research community has started looking into key questions on energy efficiency of communication networks. The European Commission activated under the FP7 the TREND Network of Excellence with the goal of establishing the integration of the EU research community in green networking with a long perspective to consolidate the European leadership in the field. TREND integrates the activities of major European players in networking, including manufacturers, operators, research centers, to quantitatively assess the energy demand of current and future telecom infrastructures, and to design energy-efficient, scalable and sustainable future networks. This paper describes the main results of the TREND research community and concludes with a roadmap describing the next steps for standardization, regulation agencies and research in both academia and industry.The research leading to these results has received funding from the EU 7th Framework Programme (FP7/2007–2013) under Grant Agreement No. 257740 (NoE TREND)

    Analysis of Energy Consumption Using Sequential to Better Signal (SBS) Scheme for Green Celluler Network

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    Over time, cellular communication technology developed significantly from year to year. This is due to increasing the number of users and the higher needed. To overcome this problem, many providers increase the number of new base station installations to fill up the customer's needed. The increase number of base stations does not take into account the amount of power consumption produced, where in the cellular network Base Stations (BS) are the most dominant energy consuming equipment estimated at 60% - 80% of the total energy consumption in the cellular industry. In addition, energy waste often occurs in the BS where the emission power will always remain even if the number of users is small. Power consumption and energy savings are important issues at this time because they will affect CO2 emissions in the air. This paper proposes to save energy consumption from BS by turning off BS (sleep mode) if the number of users is small and distributed to other BS (neighboring BS) which is called cell zooming technique. The cell size can zoom out when the load traffic is high and zoom in when the load traffic is low. To determine the central BS and neighboring BS, a sequential to better signal (SBS) scheme is used where this scheme sorts neighboring BS based on the SINR value received (user). The results of this research, base station can be able to save energy 29.12% and reduce CO2 emission around 3580 kg/year.  It means saving energy consumption which is also reducing air pollution occurs and this term can be named as green cellular network.&nbsp

    An Overview of Cell Zooming Algorithms and Power Saving Capabilities in Wireless Networks

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    Cell zooming has emerged as a potential strategy to develop a green communication system in our society and it has become an essential research area of wireless communication. Aiming to highlight the trend of existing cell zooming algorithms and their power saving capabilities, this paper reviews a number of cell zooming algorithms that have been proposed in the literature. Static cell zooming algorithms are effective for off-peak hours and their maximum power saving capability is 50% since off-peak duration is typically not more than 12 hours.Meanwhile dynamic cell zooming algorithms are applicable in full-day operation and they are useful not only for power saving but also for load balancing. However, on/off switching delay, signalling overhead due to traffic information exchange and how to attain information of traffic spatial distribution are existing challenges in dynamic cell zooming algorithms. One noticeable point is that relative power saving in dynamic cell zooming algorithm is less than 50% if traffic spatial distribution is considered. Since location management (LM) was designed for effectively servicing to customers, further researches could lead to work on location management (LM) based cell zooming algorithms for both effective servicing and energy saving

    Optimal Cell Clustering and Activation for Energy Saving in Load-Coupled Wireless Networks

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    Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study optimal cell clustering and scheduling of activation duration for each cluster, with the objective of minimizing the sum energy, subject to a time constraint of delivering the users' traffic demand. The cells within a cluster are simultaneously in transmission and napping modes, with cluster activation and deactivation, respectively. Our optimization framework accounts for the coupling relation among cells due to the mutual interference. Thus, the users' achievable rates in a cell depend on the cluster composition. On the theoretical side, we provide mathematical formulation and structural characterization for the energy-efficient cell clustering and scheduling optimization problem, and prove its NP hardness. On the algorithmic side, we first show how column generation facilitates problem solving, and then present our notion of local enumeration as a flexible and effective means for dealing with the trade-off between optimality and the combinatorial nature of cluster formation, as well as for the purpose of gauging the deviation from optimality. Numerical results demonstrate that our solutions achieve more than 60% energy saving over existing schemes, and that the solutions we obtain are within a few percent of deviation from global optimum.Comment: Revision, IEEE Transactions on Wireless Communication
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