Optimizing Service Differentiation Scheme with Sized-based Queue Management in DiffServ Networks

In this paper we introduced Modified Sized-based Queue Management as a dropping scheme that aims to fairly prioritize and allocate more service to VoIP traffic over bulk data like FTP as the former one usually has small packet size with less impact to the network congestion. In the same time, we want to guarantee that this prioritization is fair enough for both traffic types. On the other hand we study the total link delay over the congestive link with the attempt to alleviate this congestion as much as possible at the by function of early congestion notification. Our M-SQM scheme has been evaluated with NS2 experiments to measure the packets received from both and total link-delay for different traffic. The performance evaluation results of M-SQM have been validated and graphically compared with the performance of other three legacy AQMs (RED, RIO, and PI). It is depicted that our M-SQM outperformed these AQMs in providing QoS level of service differentiation.Comment: 10 pages, 9 figures, 1 table, Submitted to Journal of Telecommunication

Implementation of secure email server in cloud environment

In the recent virtual communication world, the email services play a vital role as a basic content of heterogeneous networking infrastructure. Whereby, multiple platforms are connecting each other. Mail Server refers to computer performing Mail Transfer Agent functions. MTA is software that delivers electronic mail messages from one computer to another, by using client-server application architecture. MTA implements both sender and receiver portions of SMTP (Simple Mail Transfer Protocol). Postfix is a free and open-source MTA which is fast, easy-to-administrator and provide secure communication over Internet. In this paper we focus on the problem of email contents disclosure, and establish a secure mail server by using Postfix in Linux platform and then implement it into a cloud service provider as IaaS (Infrastructure as a Service). Security is provided by tuning a Transport Layer Security (TLS), and SMTP-AUTH which use Simple Authentication and Security Layer (SASL) as a security mechanism and platform

Investigation of theoretical scaling laws using large eddy simulations for airborne spreading of viral contagion from sneezing and coughing

Using a set of large eddy point-particle simulations, we explore the fluid dynamics of an ejected puff resulting from a cough/sneeze. The ejection contains over 61 000 potentially virus-laden droplets at an injection Reynolds number of about 46 000, comparable to an actual cough/sneeze. We observe that global puff properties, such as centroid, puff volume, momentum, and buoyancy vary little across realizations. Other properties, such as maximum extent, shape, and edge velocity of the puff, may exhibit substantial variation. In many realizations, a portion of the puff splits off and advances along a random direction, while keeping airborne droplet nuclei afloat. This peeled-off portion provides a mechanism for virus-laden droplets to travel over large distances in a short amount of time. We also observe that the vast majority of droplets remain suspended within the puff after all liquid has evaporated. The main objectives of the study are to (i) evaluate assumptions of Balachandar\u27s et al. theory [Int. J. Multiphase Flow 132, 103439 (2020)], which include buoyancy effects, shape of the puff, and droplet evaporation rate, (ii) obtain values of closure parameters, which include location and time of the virtual origin, and puff entrainment and drag coefficients, and (iii) evaluate the accuracy of the theory in predicting the shape, size, and location of the puff, as well as droplet number density long after ejection. The theory adequately predicts global puff properties including size, velocity, and distance traveled, the largest size of droplets that exit the puff due to settling, and the droplet size distribution within the puff long after ejection

Gaussian mixture models and machine learning predict megakaryocytic growth and differentiation potential ex vivo

The ability to analyze single cells via flow cytometry has resulted in a wide range of biological and medical applications. Currently, there is no established framework to compare and interpret time-series flow cytometry data for cell engineering applications. Manual analysis of temporal trends is time-consuming and subjective for large-scale datasets. We resolved this bottleneck by developing TEmporal Gaussian Mixture models (TEGM), an unbiased computational strategy to quantify and predict temporal trends of developing cell subpopulations indicative of cellular phenotype. TEGM applies Gaussian mixture models and gradient boosted trees for cell engineering applications. TEGM enables the extraction of subtle features, such as the dispersion and rate of change of surface marker expression for each subpopulation over time. These critical, yet hard-to-discern, features are fed into machine-learning algorithms that predict underlying cell classes. Our framework can be flexibly applied to conventional flow cytometry sampling schemes, and allows for faster and more consistent processing of time-series flow cytometry data. Please click Additional Files below to see the full abstract

Using Gaussian mixture models and machine learning to predict donor- dependent megakaryocytic cell growth and differentiation potential ex vivo

The ability to analyze single cells via flow cytometry has resulted in a wide range of biological and medical applications. Currently, there is no established framework to compare and interpret time-series flow cytometry data for cell engineering applications. Manual analysis of temporal trends is time-consuming and subjective for large-scale datasets. We resolved this bottleneck by developing TEmporal Gaussian Mixture models (TEGM), an unbiased computational strategy to quantify and predict temporal trends of developing cell subpopulations indicative of cellular phenotype.. Please click Additional Files below to see the full abstract

Two-level QoS-aware frame-based downlink resources allocation for RT/NRT services fairness in LTE networks

In LTE, bandwidth resources allocation became a huge burden to be handled, as both of RT and NRT traffic should be processed fairly to satisfy their diverse QoS requirements. To tackle this issue in particular, in this work, we propose a fairness-based resources allocation method named Frame-based Game Theory (FGT), which can be flexibly implemented as an upper level in LTE downlink MAC layer; before the PRBs allocation function. Basically, FGT aim is to allow involved classes with different QoS requirements to fairly gain a part of the available channel resources to transmit their flows. Adhere, on every LTE-frame, a cooperative game scenario is designed. Wherein, Shapley formula is used to distribute the available amount of data within RT and NRT traffic classes. Then, conforming to these assigned resources portions to each traffic class, PRBs allocation process is triggered every TTI for the selected flows. In this work, we adopted some of the recent PRBs allocation methods as a lower level scheduler in order to illustrate a complete idea of MAC layer scheduling functions, and also to effectively evaluate FGT performance. Simulation results on various scenarios show that, fairness index for flows from different classes is increased when FGT is considered. The results also conveyed outperforming QoS indices for FGT on RT and NRT service in terms of throughput, PLR, as well as cell spectrum efficiency

Ultra-small fatty acid-stabilized magnetite nanocolloids synthesized by in situ hydrolytic precipitation

© 2015 Kheireddine El-Boubbou et al. Simple, fast, large-scale, and cost-effective preparation of uniform controlled magnetic nanoparticles remains a major hurdle on the way towards magnetically targeted applications at realistic technical conditions. Herein, we present a unique one-pot approach that relies on simple basic hydrolytic in situ coprecipitation of inexpensive metal salts (Fe<sup>2+</sup> and Fe<sup>3+</sup>) compartmentalized by stabilizing fatty acids and aided by the presence of alkylamines. The synthesis was performed at relatively low temperatures (80°C) without the use of high-boiling point solvents and elevated temperatures. This method allowed for the production of ultra-small, colloidal, and hydrophobically stabilized magnetite metal oxide nanoparticles readily dispersed in organic solvents. The results reveal that the obtained magnetite nanoparticles exhibit narrow size distributions, good monodispersities, high saturation magnetizations, and excellent colloidal stabilities. When the [fatty acid]: [Fe] ratio was varied, control over nanoparticle diameters within the range of 2-10 nm was achieved. The amount of fatty acid and alkylamine used during the reaction proved critical in governing morphology, dispersity, uniformity, and colloidal stability. Upon exchange with water-soluble polymers, the ultra-small sized particles become biologically relevant, with great promise for theranostic applications as imaging and magnetically targeted delivery vehicles

Link adaptive power control and allocation for energy–efficient downlink transmissions in LTE systems

It is axiomatic that providing more transmission power by the cell, returns high data rates; but in contrary, more power is consumed which leads to energy exhaustion. The Quality of Service (QoS) in long term evolution urban macrocell networks gives a high concern to green communication by wisely utilizing the limited cell power to improve network performance. Nevertheless, in conventional schemes, it is observed that the maximum power assigned to the evolved Node B (eNB) is fully utilized each time transmission interval regardless the transmitted amount of data. Consequently, a high level of power dissipation commonly occurs at the eNB that is caused by either an unused allocated power or an excessive subchannel power allocation which is beyond the required portion for data blocks transmission. Therefore, in this paper, we propose an efficient scheme, namely link adaptive power control and allocation (LaPCA) to mitigate the overused transmission power of the cell, and thereby, enhancing system energy efficiency while maintaining a good QoS level. The main principle in LaPCA is to control the portion of cell transmission power to be proportional to the volume of data flows that are nominated for transmission during the scheduling process. This power is then distributed over the allocated subchannels by means of nonconvex optimization to enhance system performance. System-level simulations reveal that LaPCA achieves an outstanding energy efficiency and maintains an increased throughput level and low loss ratio as more traffic load is offered to the network

Energy-aware subchannels power allocation for downlink transmissions in OFDMA systems

It is arbitrarily known that the spectrum scarcity issue in the wireless channel has brought to the surface several Quality of Service (QoS)-related challenges for the network operators. Although it is claimed a QoS improvement may be possible if a high wireless signal frequency is generated, this solution does not seem to be compatible with the emerged network scenarios, wherein low power and energy-efficient communications are among the core driving QoS criteria. Minding that, in this paper, we look into the problem of subchannel power allocation at the downlink LTE-A network. Accordingly, an Energy-aware Subchannels Power Allocation (EaSPA) algorithm is proposed to solve the formulated non-convex optimization problem. The system-level simulation experiments imply that the proposed subchannels power allocation model enhances the energy efficiency by 20% compared with a reference scheme. In addition, a low dissipated power level is preserved over different network loads

Thermal based remediation technologies for soil and groundwater: a review

Thermal remediation technologies are fast and effective tools for the remediation of contaminated soils and sediments. Nevertheless, the high energy consumption and the effect of high temperature on the soil properties may hinder the wide applications of thermal remediation methods. This review highlights the recent studies focused on thermal remediation. Eight types of thermal remediation processes are discussed, including incineration, thermal desorption, stream enhanced extraction, electrical resistance heating, microwave heating, smoldering, vitrification, and pyrol-ysis. In addition, the combination of thermal remediation with other remediation technologies is presented. Finally, thermal remediation sustainability is evaluated in terms of energy efficiency and their impact on soil properties. The developments of the past decade show that thermal-based technologies are quite effective in terms of contaminant removal but that these technologies are associated with high energy use and costs and can has an adverse impact on soil properties. Nonetheless, it is anticipated that continued research on thermally based technologies can increase their sustainability and expand their applications. Low temperature thermal desorption is a prom-ising remediation technology in terms of land use and energy cost as it has no adverse effect on soil function after treatment and low temperature is required. Overall, selecting the sustainable remediation technology depends on the contaminant properties, soil properties and predicted risk level. © 2022 Desalination Publications. All rights reserved