59,548 research outputs found

    Green Cellular Networks: A Survey, Some Research Issues and Challenges

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    Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

    SOTXTSTREAM: Density-based self-organizing clustering of text streams

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    A streaming data clustering algorithm is presented building upon the density-based selforganizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets

    Ring Resonators with Sagnac Loops for Photonic Processing in DWDM Backbone Networks

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    In this paper, optical configurations based on ring resonators (RR) with an internal Sagnac (SG) loop in the feedback path, are analyzed in terms of their amplitude response and dispersive properties for filtering and chromatic dispersion managing in digital transmission systems over amplified single- mode fiber (SMF) spans in DWDM backbone networks. Design issues for the architecture as regards quadratic dispersion and magnitude distortion are provided. The RR+SG compound filter provides frequency tunability of the amplitude and dispersion peaks by adjusting a coupling coefficient of an optical coupler, with no need for using integrated thermo-optic nor current- injection based phase shifters. The configuration can be employed as an additional structure for a general RR-based design and synthesis architecture, allowing bandwidth increase of dispersion compensators and flexibility. The performance of a compound filter consisting of a two RR in series stage and a RR+SG filter are reported as a more compact and effective solution for existing multi-channel SMF backbone links operating at high bit rates. Design guidelines of an integrated ring resonator based on polymer technology for showing feasibility of the proposal is reported.This work was partially supported by Spanish CICYT (TEC2006-13273-C03-03-MIC), European project NoE EPhoton/One+, CAM (FACTOTEM-CM:S-0505/ESP/000417), FENIS-CCG06-UC3MITIC-0619.Publicad

    Locally Self-Adjusting Skip Graphs

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    We present a distributed self-adjusting algorithm for skip graphs that minimizes the average routing costs between arbitrary communication pairs by performing topological adaptation to the communication pattern. Our algorithm is fully decentralized, conforms to the CONGEST\mathcal{CONGEST} model (i.e. uses O(logn)O(\log n) bit messages), and requires O(logn)O(\log n) bits of memory for each node, where nn is the total number of nodes. Upon each communication request, our algorithm first establishes communication by using the standard skip graph routing, and then locally and partially reconstructs the skip graph topology to perform topological adaptation. We propose a computational model for such algorithms, as well as a yardstick (working set property) to evaluate them. Our working set property can also be used to evaluate self-adjusting algorithms for other graph classes where multiple tree-like subgraphs overlap (e.g. hypercube networks). We derive a lower bound of the amortized routing cost for any algorithm that follows our model and serves an unknown sequence of communication requests. We show that the routing cost of our algorithm is at most a constant factor more than the amortized routing cost of any algorithm conforming to our computational model. We also show that the expected transformation cost for our algorithm is at most a logarithmic factor more than the amortized routing cost of any algorithm conforming to our computational model

    Application of a simplified thermal-electric model of a sodium-nickel chloride battery energy storage system to a real case residential prosumer

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    Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the self-consumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl2 battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodium-nickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market
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