Modeling the interaction between TCP and Rate Adaptation

In this paper, we model and investigate the interaction between the TCP protocol and rate adaptation at intermediate routers. Rate adaptation aims at saving energy by controlling the offered capacity of links and adapting it to the amount of traffic. However, when TCP is used at the transport layer, the control loop of rate adaptation and one of the TCP congestion control mechanism might interact and disturb each other, compromising throughput and Quality of Service (QoS). Our investigation is lead through mathematical modeling consisting in depicting the behavior of TCP and of rate adaption through a set of Delay Differential Equations (DDEs). The model is validated against simulation results and it is shown to be accurate. The results of the sensitivity analysis of the system performance to control parameters show that rate adaptation can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair QoS

From Measurements to Modeling The Trade-off between Energy Efficiency and System Performance

In this thesis, the work is based on experimental and modeling methodologies. I applied this starting from measurements of Asymmetric Digital Subscriber Line (ADSL) technology, which is the preferred high-speed access to the Internet. The work focuses on the problem of determining the maximum stable bandwidth that an Internet Service Provider (ISP) can offer. This task was accomplished by monitoring and analyzing a large set of ADSL end-users. Huge amount of collected data allowed us to get a detailed statistical analysis of the behavior of ADSL lines, such as the distribution, variable dependencies and correlation of effective bitrate with the physical measurements exposed by network devices. Analysis of collected data suggest that there is no clear trend to predict a downstream bandwidth of ADSL line based on line conditions, and thus requires an intelligent way of analyzing the ADSL lines. Thus, a Neural Network (NN) was employed, which is an intelligent machine learning tool to (i) learn the behavior of ADSL lines, (ii) extract useful information from huge set of measurements, (iii) automatically suggest maximum stable bandwidth. The results indicate that NN performs well in predicting end-users available bandwidth. However, NN is required to be properly trained, as well as needs careful selection of design parameters. Later, the focus of the work was centered over the energy efficiency of telecommunication systems using mathematical modeling approach. Motivation of first work was to know how much energy efficient is Voice over Internet Protocol (VoIP) architecture as compared to traditional Public-Switched Telephone Network (PSTN) architecture used for voice communication. To answer this, these two architectures already implemented at our campus were extensively examined by means of measuring real power consumption. To generalize or estimate power consumption for any given number of users, a mathematical model of power consumption for both the architectures is built. The results indicate that VoIP architecture consumes a lot of power, yet VoIP system have the flexibility to be made energy efficient by adding some sort of energy-wise schemes. The last part of the work investigates the interaction between the Transmission Control Protocol (TCP) and rate adaptation mechanism. Where rate adaptation is an approach to save energy by adapting the transmission rates or capacity according to traffic dynamics. To have deep insight of the interaction, a mathematical model based on fluid based framework is built to depict the behavior of TCP and rate adaptation scheme. The model is then tested for its accuracy and stability by conducting simulation experiments and steady state analysis. Later, the model is used to study the impact of tuning the parameters on system performance. The results suggest that the implementation of rate adaptation scheme can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair QoS

From Measurements to Modeling The Trade-off between Energy Efficiency and System Performance

In this thesis, the work is based on experimental and modeling methodologies. I applied this starting from measurements of Asymmetric Digital Subscriber Line (ADSL) technology, which is the preferred high-speed access to the Internet. The work focuses on the problem of determining the maximum stable bandwidth that an Internet Service Provider (ISP) can offer. This task was accomplished by monitoring and analyzing a large set of ADSL end-users. Huge amount of collected data allowed us to get a detailed statistical analysis of the behavior of ADSL lines, such as the distribution, variable dependencies and correlation of effective bitrate with the physical measurements exposed by network devices. Analysis of collected data suggest that there is no clear trend to predict a downstream bandwidth of ADSL line based on line conditions, and thus requires an intelligent way of analyzing the ADSL lines. Thus, a Neural Network (NN) was employed, which is an intelligent machine learning tool to (i) learn the behavior of ADSL lines, (ii) extract useful information from huge set of measurements, (iii) automatically suggest maximum stable bandwidth. The results indicate that NN performs well in predicting end-users available bandwidth. However, NN is required to be properly trained, as well as needs careful selection of design parameters. Later, the focus of the work was centered over the energy efficiency of telecommunication systems using mathematical modeling approach. Motivation of first work was to know how much energy efficient is Voice over Internet Protocol (VoIP) architecture as compared to traditional Public-Switched Telephone Network (PSTN) architecture used for voice communication. To answer this, these two architectures already implemented at our campus were extensively examined by means of measuring real power consumption. To generalize or estimate power consumption for any given number of users, a mathematical model of power consumption for both the architectures is built. The results indicate that VoIP architecture consumes a lot of power, yet VoIP system have the flexibility to be made energy efficient by adding some sort of energy-wise schemes. The last part of the work investigates the interaction between the Transmission Control Protocol (TCP) and rate adaptation mechanism. Where rate adaptation is an approach to save energy by adapting the transmission rates or capacity according to traffic dynamics. To have deep insight of the interaction, a mathematical model based on fluid based framework is built to depict the behavior of TCP and rate adaptation scheme. The model is then tested for its accuracy and stability by conducting simulation experiments and steady state analysis. Later, the model is used to study the impact of tuning the parameters on system performance. The results suggest that the implementation of rate adaptation scheme can be effective but a careful parameter setting is needed to avoid undesired disruptive interaction among controllers at different levels, that impair Qo

A Novel Micellar Electrokinetic Chromatographic Method for Separation of Metal-DDTC Complexes

Micellar electrokinetic chromatography (MEKC) was examined for the separation and determination of Mo(VI), Cr(VI), Ni(II), Pd(II), and Co(III) as diethyl dithiocarbamate (DDTC) chelates. The separation was achieved from fused silica capillary (52 cm × 75 μm id) with effective length 40 cm, background electrolyte (BGE) borate buffer pH 9.1 (25 mM), CTAB 30% (100 mM), and 1% butanol in methanol (70 : 30 : 5 v/v/v) with applied voltage of −10 kV using reverse polarity. The photodiode array detection was achieved at 225 nm. The linear calibration for each of the element was obtained within 0.16–10 μg/mL with a limit of detection (LOD) 0.005–0.0167 μg/mL. The separation and determination was repeatable with relative standard deviation (RSD) within 2.4–3.3% (n = 4) in terms of migration time and peak height/peak area. The method was applied for the determination of Mo(VI) from potatoes and almond, Ni(II) from hydrogenated vegetable oil, and Co(III) from pharmaceutical preparations with RSD within 3.9%. The results obtained were checked by standard addition and rechecked by atomic absorption spectrometry

HPLC Determination of α-keto Acids in Human Serum and Urine after Derivatization with 4-Nitro-1,2-phenylenediamine

The determination of α-keto acids has clinical importance, because these are intermediates in a number of biochemical processes. This work reports the development of an HPLC procedure for the analysis α-keto acids in blood and urine samples after derivatization with 4-nitro-1,2-phenylenediamine (NPD). Nine α-keto acids: glyoxylic acid (GA), pyruvic acid (PYR), 2-oxobutyric acid (KB), 3-methyl-2-oxobutyric acid (MKBA), 3-methyl-2-oxovaleric acid (K3MVA), 2-oxoglutaric acid (KG), 4-methyl-2-oxovaleric acid (K4MVA), 2-oxohexanoic acid (KHA) and phenylpyruvic acid (PPY) were derivatized with (NPD) at pH 3 and separated on a Zorbax 300 SB-C18 HPLC column (4.6x150mm id) and photodiode array detection at 255 nm. The isocratic elution was performed with methanol: water: acetonitrile (42: 56:2, v/ v/ v) with a flow rate 0.9 mL/min. The keto acids separated within 14 min. The method was repeatable with a relative standard deviation (RSD) of 0.1-2.9% for each of the α-keto acids. The limits of detection and quantitation were obtained within the range 0.05-0.26 µg/ mL and 0.15-0.8 µg/ mL respectively. The method was applied for determination of α-keto acids from a pharmaceutical preparation, human serum and urine samples of healthy volunteers and diabetic patients. The results were further confirmed by standard addition technique. The method is rapid and simple and is suitable for the separation and determination of α-keto acids from clinical samples

Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition

Human Activity Recognition has a long history of research and requires further exploration to produce useful and optimal outcomes. Areas such as medicine, daily routine, and security are some benefits that smartphone enables via embedded sensors. Our work has chosen sensor data of six activities such as standing, walking, laying from pre-recorded dataset gathered via smartphone to evaluate the performance of various supervised machine learning algorithms. The results suggest that logistic regression has been an optimal choice based on experiments. Whereas, the Support Vector Machine (SVM) has shown to perform well with ninety-five percentage accuracy

ISSN-1996-918X Pak

Abstract Banana peel, a common fruit waste has been investigated to remove and preconcentrate Cr(III) from industrial wastewater. It was characterized by FT-IR spectroscopy. The parameters pH, contact time, initial metal ion concentration and temperature were investigated and the maximum sorption was found to be 95%. The binding of metal ions was found to be pH dependent with the optimal sorption occurring at pH 4. The retained species were eluted using 5mL of 2 M HNO 3 . The mechanism for the binding of Cr(III) on the banana peel surface was also studied in detail. The Langmuir and Dubinin-Radushkevich (D-R) isotherms were used to describe the partitioning behavior for the system at different temperatures. Kinetic and thermodynamic measurements of the banana peel for chromium ions were also studied. The method was applied for the removal and preconcentration of Cr(III) from industrial wastewater

Cathodic Stripping Voltammetric Determination of Cefadroxil in Pharmaceutical Preparations and in Blood Serum

Abstract An analytical method has been developed using hanging mercury drop electrode (HMDE) for the quantitative determination of antibacterial drug cefadroxil (CFL) from pharmaceutical preparations and blood serum. Cathodic adsorptive stripping voltammetry was carried out in hydrochloric acid (0.1M): methanol (80: 20 v/v) and potassium chloride (0.1M) as supporting electrolyte. The reduction wave was obtained within -700 to -800 mV. Linear calibration curve was within 1-50µg/mL with detection limit of 0.1µg/mL of cefadroxil. Relative standard deviation for inter and intra day analysis of CFL was within 1-2%. The number of additives present in pharmaceutical preparations did not interfere the determination of cefadroxil. The analysis of pharmaceutical preparations and blood serum after chemotherapy with cefadroxil indicated relative standard deviation (RSD) within 0.8-1.2% and 2.6-3.8% respectively. The satisfactory results were obtained for quality control of cefadroxil in pharmaceutical preparations and in blood serum