scholarly journals Estimation of Spectrum Requirements for Mobile Networks With Self-Similar Traffic, Handover, and Frequency Reuse

2010 ◽  
Vol 6 (4) ◽  
pp. 281-291
Author(s):  
Won Seok Yang ◽  
Eun Saem Yang ◽  
Hwa J. Kim ◽  
Dae K. Kim
Keyword(s):  
Mobile Networks ◽  
Probability Distributions ◽  
Frequency Reuse ◽  
Estimation Methods ◽  
Data Traffic ◽  
Load Spectrum ◽  
Self Similarity ◽  
Average Cell ◽  
Self Similar ◽  
The Impact

This paper considers self-similarity in data traffic, handover, and frequency reuse to estimate the spectrum requirements of mobile networks. An approximate average cell capacity subject to a delay requirement and self-similar traffic is presented. It is shown that handover traffic can be an additional load. Spectrum requirements are calculated based on carrier demand instead of spectral efficiency, as at least one carrier is necessary to transmit even 1 bit. The cell-split operation is considered under frequency reuse of one. Estimation methods are presented using cell traffic in two cases. First, a procedure is presented that estimates cell traffic from previous networks. Second, cell traffic is assumed to follow probability distributions. Numerical examples demonstrate the impact of self-similarity, handover, and the proportion of cell-split occurrences on the spectrum requirements.

Study of the Impact of Self-Similarity on the Network Node Traffic

1970 ◽  
Vol 111 (5) ◽  
pp. 27-32
Author(s):  
L. Kaklauskas ◽  
L. Sakalauskas
Keyword(s):  
Network Traffic ◽  
Buffer Capacity ◽  
Service Discipline ◽  
Network Node ◽  
Self Similarity ◽  
Packet Losses ◽  
Queue Discipline ◽  
Self Similar ◽  
Stochastically Bounded ◽  
The Impact

The article analyses a stochastically bounded the GI/G/m//N circuit switched network model with packet losses, with stochastic input network traffic, stochastic served network node, and deterministic and finite network node buffer capacity. Max-plus algebra instrumentality is used for the network processes analysis. FIFO tail drop or LIFO tail drop buffer is used. We have established that the average waiting time in the queue had increased when the queue service discipline was FIFO as compared with LIFO, while the offered traffic was Poisson and the served in the node traffic was self-similar. The network traffic is served faster in the network node with the buffer queue discipline LIFO, while the offered traffic is Poisson and its intensity exceeds the served in the node traffic 10 times. Ill. 2, bibl. 24 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.111.5.350

scholarly journals Developing a Framework for Future Mobile Data Pricing

2017 ◽  
Vol 21 (2) ◽  
pp. 84 ◽  
Author(s):  
Michael Paetsch ◽  
Peter Dorčák ◽  
František Pollák ◽  
Ľubomír Štrba ◽  
Branislav Kršák
Keyword(s):  
Mobile Networks ◽  
Economic Value ◽  
Network Capacity ◽  
Data Traffic ◽  
Fixed Amount ◽  
Mobile Data ◽  
Data Value ◽  
Voice Calls ◽  
The Impact ◽  
New Framework

<p><strong>Purpose:</strong> The revenues for mobile data transmission overtook the revenue of voice calls for the first time in 2014 in the USA. It can be observed that demand for mobile data – largely driven by video and cloud - is increasing exponentially, while overall data revenue is rising only moderately. This will lead to insufficient revenues stream to increase investments into mobile networks and ensure quality service. Consequently, hereof network performance will deteriorate sharply. At the heart of the problem is the current global pricing regime of fixed multiple MB/GB bundles, irrespective of time of the day, intensity of usage (e.g. video vs. email) and underlying economic value of the data. A new framework is proposed as to optimize and align network capacity and implicit data value/utility, which is crucial to ensure customer satisfaction and access justice.</p><p><strong>Methodology/Approach:</strong> The fundamental differences in pricing voice and data in voice and/or data centric networks are analysed in detail. Information has been synthesized as to develop insights into the impact of different devises and type of digital traffic for the overall performance of mobile networks. Based hereupon, a new framework for mobile data has been proposed to address the increasing misalignment between network capacity, usage and underlying data value/utility. Initial solutions have been proposed and discussed.</p><p><strong>Findings:</strong> While voice calls are easily quantifiable and are largely predictable in its occurrence and network load implications, mobile data traffic shows very large variations depending on type of traffic. While social media messaging by many customers consumes very little capacity, consumption of video streaming by relatively few customers can lead already to network saturation.</p><p><strong>Research Limitation/implication:</strong> Carriers set prices for a fixed amount of data – irrespective of intensity and time of data traffic - which leads to sharp spiky type of traffic patterns essentially signalling sharp overuse during busy hours coexist with large period of underused times.</p><strong>Originality/Value of paper:</strong> A new framework for proposition building and particularly pricing of mobile data services is provided.

scholarly journals Information Theory for Non-Stationary Processes with Stationary Increments

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1223 ◽  
Author(s):  
Carlos Granero-Belinchón ◽  
Stéphane G. Roux ◽  
Nicolas B. Garnier
Keyword(s):  
Information Theory ◽  
Probability Distributions ◽  
Entropy Rate ◽  
Integration Time ◽  
Stationary Processes ◽  
Self Similarity ◽  
Single Realization ◽  
Self Similar ◽  
Non Gaussian ◽  
Do So

We describe how to analyze the wide class of non-stationary processes with stationary centered increments using Shannon information theory. To do so, we use a practical viewpoint and define ersatz quantities from time-averaged probability distributions. These ersatz versions of entropy, mutual information, and entropy rate can be estimated when only a single realization of the process is available. We abundantly illustrate our approach by analyzing Gaussian and non-Gaussian self-similar signals, as well as multi-fractal signals. Using Gaussian signals allows us to check that our approach is robust in the sense that all quantities behave as expected from analytical derivations. Using the stationarity (independence on the integration time) of the ersatz entropy rate, we show that this quantity is not only able to fine probe the self-similarity of the process, but also offers a new way to quantify the multi-fractality.

Asteroid and Comet Impact Speeds upon Mars: Significance for Panspermia and the Supply of Organics

1997 ◽  
Vol 161 ◽  
pp. 197-201 ◽  
Author(s):  
Duncan Steel
Keyword(s):  
Probability Distributions ◽  
Regions Of Interest ◽  
Significant Fraction ◽  
Organic Chemicals ◽  
Impact Speed ◽  
The Mean ◽  
The Impact

AbstractWhilst lithopanspermia depends upon massive impacts occurring at a speed above some limit, the intact delivery of organic chemicals or other volatiles to a planet requires the impact speed to be below some other limit such that a significant fraction of that material escapes destruction. Thus the two opposite ends of the impact speed distributions are the regions of interest in the bioastronomical context, whereas much modelling work on impacts delivers, or makes use of, only the mean speed. Here the probability distributions of impact speeds upon Mars are calculated for (i) the orbital distribution of known asteroids; and (ii) the expected distribution of near-parabolic cometary orbits. It is found that cometary impacts are far more likely to eject rocks from Mars (over 99 percent of the cometary impacts are at speeds above 20 km/sec, but at most 5 percent of the asteroidal impacts); paradoxically, the objects impacting at speeds low enough to make organic/volatile survival possible (the asteroids) are those which are depleted in such species.

The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 89-99 ◽  
Author(s):  
Leslie Rutkowski ◽  
Yan Zhou
Keyword(s):  
Sparse Matrix ◽  
Small Body ◽  
Auxiliary Information ◽  
Poor Quality ◽  
Quality Data ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Population Parameter ◽  
Conditioning Model ◽  
The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

scholarly journals Morphological, thermal and mechanical properties of recycled HDPE foams via rotational molding

2021 ◽  
pp. 0021955X2110137
Author(s):  
Yao Dou ◽  
Denis Rodrigue
Keyword(s):  
Cell Density ◽  
Morphological Analysis ◽  
Mechanical Characterization ◽  
Gradual Increase ◽  
Thermal And Mechanical Properties ◽  
Rotational Molding ◽  
Average Cell Size ◽  
Average Cell ◽  
The Impact ◽  
Recycled Hdpe

In this study, foamed recycled high density polyethylene (rHDPE) parts were produced by rotational molding using different concentration (0 to 1% wt.) of a chemical blowing agent (CBA) based on azodicarbonamide. From the samples produced, a complete morphological, thermal and mechanical characterization was performed. The morphological analysis showed a gradual increase in the average cell size, while the cell density firstly increased and then decreased with increasing CBA content. As expected, increasing the CBA content decreased the foam density as well as the thermal conductivity. Although increasing the CBA content decreased both tensile and flexural properties, the impact strength showed a similar trend as the cell density with an optimum CBA content around 0.1% wt. Finally, neat rHDPE samples were also produced by compression molding. The results showed negligible differences between the rotomolded and compression molded properties indicating that optimal rotomolding conditions were selected. These results confirm the possibility of using 100% recycled polymers to produce rotomolded foam parts.

scholarly journals Statistical Analysis and Machine Learning Prediction of Fog-Caused Low-Visibility Events at A-8 Motor-Road in Spain

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 679
Author(s):  
Sara Cornejo-Bueno ◽  
David Casillas-Pérez ◽  
Laura Cornejo-Bueno ◽  
Mihaela I. Chidean ◽  
Antonio J. Caamaño ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Probability Distributions ◽  
Pearson Correlation ◽  
Likelihood Method ◽  
Neural Network Approach ◽  
Event Duration ◽  
Full Characterization ◽  
Low Visibility ◽  
Learning Machine ◽  
The Impact

This work presents a full statistical analysis and accurate prediction of low-visibility events due to fog, at the A-8 motor-road in Mondoñedo (Galicia, Spain). The present analysis covers two years of study, considering visibility time series and exogenous variables collected in the zone affected the most by extreme low-visibility events. This paper has then a two-fold objective: first, we carry out a statistical analysis for estimating the fittest probability distributions to the fog event duration, using the Maximum Likelihood method and an alternative method known as the L-moments method. This statistical study allows association of the low-visibility depth with the event duration, showing a clear relationship, which can be modeled with distributions for extremes such as Generalized Extreme Value and Generalized Pareto distributions. Second, we apply a neural network approach, trained by means of the ELM (Extreme Learning Machine) algorithm, to predict the occurrence of low-visibility events due to fog, from atmospheric predictive variables. This study provides a full characterization of fog events at this motor-road, in which orographic fog is predominant, causing important traffic problems during all year. We also show how the ELM approach is able to obtain highly accurate low-visibility events predictions, with a Pearson correlation coefficient of 0.8, within a half-hour time horizon, enough to initialize some protocols aiming at reducing the impact of these extreme events in the traffic of the A-8 motor road.

scholarly journals Measuring Key Quality Indicators in Cloud Gaming: Framework and Assessment Over Wireless Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1387
Author(s):  
Oswaldo Sebastian Peñaherrera-Pulla ◽  
Carlos Baena ◽  
Sergio Fortes ◽  
Eduardo Baena ◽  
Raquel Barco
Keyword(s):  
Communication Networks ◽  
Mobile Networks ◽  
Video Game ◽  
Know How ◽  
Fifth Generation ◽  
New Generation ◽  
Graphics Rendering ◽  
The Impact

Cloud Gaming is a cutting-edge paradigm in the video game provision where the graphics rendering and logic are computed in the cloud. This allows a user’s thin client systems with much more limited capabilities to offer a comparable experience with traditional local and online gaming but using reduced hardware requirements. In contrast, this approach stresses the communication networks between the client and the cloud. In this context, it is necessary to know how to configure the network in order to provide service with the best quality. To that end, the present work defines a novel framework for Cloud Gaming performance evaluation. This system is implemented in a real testbed and evaluates the Cloud Gaming approach for different transport networks (Ethernet, WiFi, and LTE (Long Term Evolution)) and scenarios, automating the acquisition of the gaming metrics. From this, the impact on the overall gaming experience is analyzed identifying the main parameters involved in its performance. Hence, the future lines for Cloud Gaming QoE-based (Quality of Experience) optimization are established, this way being of configuration, a trendy paradigm in the new-generation networks, such as 4G and 5G (Fourth and Fifth Generation of Mobile Networks).

scholarly journals The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

2021 ◽  
Vol 18 (2) ◽  
pp. 705
Author(s):  
Hongpeng Guo ◽  
Sidong Xie ◽  
Chulin Pan
Keyword(s):  
Carbon Emissions ◽  
Structural Changes ◽  
Multiple Linear Regression Model ◽  
Industry Structure ◽  
Estimation Methods ◽  
Low Carbon ◽  
Carbon Sinks ◽  
Resource Endowment ◽  
The Government ◽  
The Impact

This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions; (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.

scholarly journals Onset of the Mach Reflection of Zel’dovich–von Neumann–Döring Detonations

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 314
Author(s):  
Tianyu Jing ◽  
Huilan Ren ◽  
Jian Li
Keyword(s):  
Hot Spot ◽  
Mach Reflection ◽  
Near Field ◽  
The Self ◽  
Small Scale ◽  
Mach Stem ◽  
Self Similarity ◽  
Von Neumann ◽  
Similarity Problem ◽  
Self Similar

The present study investigates the similarity problem associated with the onset of the Mach reflection of Zel’dovich–von Neumann–Döring (ZND) detonations in the near field. The results reveal that the self-similarity in the frozen-limit regime is strictly valid only within a small scale, i.e., of the order of the induction length. The Mach reflection becomes non-self-similar during the transition of the Mach stem from “frozen” to “reactive” by coupling with the reaction zone. The triple-point trajectory first rises from the self-similar result due to compressive waves generated by the “hot spot”, and then decays after establishment of the reactive Mach stem. It is also found, by removing the restriction, that the frozen limit can be extended to a much larger distance than expected. The obtained results elucidate the physical origin of the onset of Mach reflection with chemical reactions, which has previously been observed in both experiments and numerical simulations.

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