881 resultados para network performance


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Squirmish at the Oasis takes its name from Luigi Russolo's fourth noise network 'Skirmish at the Oasis' performed in Milan in 1913. 100 years on the Agency of Noise contemplate changes in technology and the culture industry that provoke new questions around the deliberate use of noise within music and art. Through live acts of enquiry and experimentation five artists unravel paradoxes associated with the use of noise in art, music and the gallery space. The works challenge tensions, contradictions and possible oxymorons that emerge through the use and acceptance of noise within an artistic framework. Featuring: DAISY DIXON / GRAHAM DUNNING / POLLYFIBRE / DANE SUTHERLAND / MARNIE WATTS

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Long Term Evolution based networks lack native support for Circuit Switched (CS) services. The Evolved Packet System (EPS) which includes the Evolved UMTS Terrestrial Radio Access Network (E-UTRAN) and Evolved Packet Core (EPC) is a purely all-IP packet system. This introduces the problem of how to provide voice call support when a user is within an LTE network and how to ensure voice service continuity when the user moves out of LTE coverage area. Different technologies have been proposed for the purpose of providing a voice to LTE users and to ensure the service continues outside LTE networks. The aim of this paper is to analyze and evaluate the overall performance of these technologies along with Single Radio Voice Call Continuity (SRVCC) Inter-RAT handover to Universal Terrestrial Radio Access Networks/ GSM-EDGE radio access Networks (UTRAN/GERAN). The possible solutions for providing voice call and service continuity over LTE-based networks are Circuit Switched Fall Back (CSFB), Voice over LTE via Generic Access (VoLGA), Voice over LTE (VoLTE) based on IMS/MMTel with SRVCC and Over The Top (OTT) services like Skype. This paper focuses mainly on the 3GPP standard solutions to implement voice over LTE. The paper compares various aspects of these solutions and suggests a possible roadmap that mobile operators can adopt to provide seamless voice over LTE.

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Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

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tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

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Purpose – This paper aims to provide a synthetic review of the empirical literature on the multinational enterprise (MNE), subsidiaries and performance. Design/methodology/approach – The paper examines the following: the theoretical and conceptual foundation of multinationality (M) and performance (P) measures; the impact of MNE strategic investment motives on performance; the influence of contextual external and internal environment factors on performance; the strategy to optimize value chain activities of the MNE by cooperating with external partners in an asymmetric network, the key drivers of enhanced shareholder value and the implications of performance; and the need to access primary data provided by firms and managers themselves when analyzing the internal functioning of the MNE and its subsidiaries. Findings – The overall message from this literature review is that empirical research should be designed on the basis of relevant theoretical and conceptual foundations of the performance construct. Originality/value – The paper provides a systematic and synthetic review of theoretical and empirical literature.

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The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

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The network paradigm has been highly influential in spatial analysis in the globalisation era. As economies across the world have become increasingly integrated, so-called global cities have come to play a growing role as central nodes in the networked global economy. The idea that a city’s position in global networks benefits its economic performance has resulted in a competitive policy focus on promoting the economic growth of cities by improving their network connectivity. However, in spite of the attention being given to boosting city connectivity little is known about whether this directly translates to improved city economic performance and, if so, how well connected a city needs to be in order to benefit from this. In this paper we test the relationship between network connectivity and economic performance between 2000 and 2008 for cities with over 500,000 inhabitants in Europe and the USA to inform European policy.

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With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.

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The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

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Contemporary US sitcom is at an interesting crossroads: it has received an increasing amount of scholarly attention (e.g. Mills 2009; Butler 2010; Newman and Levine 2012; Vermeulen and Whitfield 2013), which largely understands it as shifting towards the aesthetically and narratively complex. At the same time, in the post-broadcasting era, US networks are particularly struggling for their audience share. With the days of blockbuster successes like Must See TV’s Friends (NBC 1994-2004) a distant dream, recent US sitcoms are instead turning towards smaller, engaged audiences. Here, a cult sensibility of intertextual in-jokes, temporal and narrational experimentation (e.g. flashbacks and alternate realities) and self-reflexive performance styles have marked shows including Community (NBC 2009-2015), How I Met Your Mother (CBS 2005-2014), New Girl (Fox 2011-present) and 30 Rock (NBC 2006-2013). However, not much critical attention has so far been paid to how these developments in textual sensibility in contemporary US sitcom may be influenced by, and influencing, the use of transmedia storytelling practices, an increasingly significant industrial concern and rising scholarly field of enquiry (e.g. Jenkins 2006; Mittell 2015; Richards 2010; Scott 2010; Jenkins, Ford and Green 2013). This chapter investigates this mutual influence between sitcom and transmedia by taking as its case studies two network shows that encourage invested viewership through their use of transtexts, namely How I Met Your Mother (hereafter HIMHM) and New Girl (hereafter NG). As such, it will pay particular attention to the most transtextually visible character/actor from each show: HIMYM’s Barney Stinson, played by Neil Patrick Harris, and NG’s Schmidt, played by Max Greenfield. This chapter argues that these sitcoms do not simply have their particular textual sensibility and also (happen to) engage with transmedia practices, but that the two are mutually informing and defining. This chapter explores the relationships and interplay between sitcom aesthetics, narratives and transmedia storytelling (or industrial transtexts), focusing on the use of multiple delivery channels in order to disperse “integral elements of a fiction” (Jenkins, 2006 95-6), by official entities such as the broadcasting channels. The chapter pays due attention to the specific production contexts of both shows and how these inform their approaches to transtexts. This chapter’s conceptual framework will be particularly concerned with how issues of texture, the reality envelope and accepted imaginative realism, as well as performance and the actor’s input inform and illuminate contemporary sitcoms and transtexts, and will be the first scholarly research to do so. It will seek out points of connections between two (thus far) separate strands of scholarship and will move discussions on transtexts beyond the usual genre studied (i.e. science-fiction and fantasy), as well as make a contribution to the growing scholarship on contemporary sitcom by approaching it from a new critical angle. On the basis that transmedia scholarship stands to benefit from widening its customary genre choice (i.e. telefantasy) for its case studies and from making more use of in-depth close analysis in its engagement with transtexts, the chapter argues that notions of texture, accepted imaginative realism and the reality envelope, as well as performance and the actor’s input deserve to be paid more attention to within transtext-related scholarship.

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This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.

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Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

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The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

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The main objective for this degree project is to implement an Application Availability Monitoring (AAM) system named Softek EnView for Fujitsu Services. The aim of implementing the AAM system is to proactively identify end user performance problems, such as application and site performance, before the actual end users experience them. No matter how well applications and sites are designed and nomatter how well they meet business requirements, they are useless to the end users if the performance is slow and/or unreliable. It is important for the customers to find out whether the end user problems are caused by the network or application malfunction. The Softek EnView was comprised of the following EnView components: Robot, Monitor, Reporter, Collector and Repository. The implemented system, however, is designed to use only some of these EnView elements: Robot, Reporter and depository. Robots can be placed at any key user location and are dedicated to customers, which means that when the number of customers increases, at the sametime the amount of Robots will increase. To make the AAM system ideal for the company to use, it was integrated with Fujitsu Services’ centralised monitoring system, BMC PATROL Enterprise Manager (PEM). That was actually the reason for deciding to drop the EnView Monitor element. After the system was fully implemented, the AAM system was ready for production. Transactions were (and are) written and deployed on Robots to simulate typical end user actions. These transactions are configured to run with certain intervals, which are defined collectively with customers. While they are driven against customers’ applicationsautomatically, transactions collect availability data and response time data all the time. In case of a failure in transactions, the robot immediately quits the transactionand writes detailed information to a log file about what went wrong and which element failed while going through an application. Then an alert is generated by a BMC PATROL Agent based on this data and is sent to the BMC PEM. Fujitsu Services’ monitoring room receives the alert, reacts to it according to the incident management process in ITIL and by alerting system specialists on critical incidents to resolve problems. As a result of the data gathered by the Robots, weekly reports, which contain detailed statistics and trend analyses of ongoing quality of IT services, is provided for the Customers.