Software‐defined networking approach for enhanced evolved packet core network

The evolved packet core (EPC) network is the mobile network standardized by the 3rd Generation Partnership Project and represents the recent evolution of mobile networks providing high‐speed data rates and on‐demand connectivity services. Software‐defined networking (SDN) is recently gaining momentum in network research as a new generation networking technique. An SDN‐based EPC is expected to introduce gains to the EPC control plane architecture in terms of simplified, and perhaps even software‐based, vendor independent infrastructure nodes. In this paper, we propose a novel SDN‐based EPC architecture along with the protocol‐level detailed implementation and provide a mechanism for identifying information fields exchanged between SDN‐EPC entities that maintains correct functionality with minimal impact on the conventional design. Furthermore, we present the first comprehensive network performance evaluation for the SDN‐based EPC versus the conventional EPC and provide a comparative analysis of 2 networks performances identifying potential bottlenecks and performance issues. The evaluation focuses on 2 network control operations, namely, the S1‐handover and registration operations, taking into account several factors, and assessing performance metrics such as end‐to‐end delay (E2ED) for completion of the respective control operation, and EPC nodes utilization figures.     

The benefits of the transition from fossil fuel to solar energy in Libya: A street lighting system case study

The Libyan economy is dominated by the oil and the gas industry which are considered as the primary energy sources for the generating power plants. With the increased energy demands in the near future, Libya will be forced to burn more oil and gas. This, in turn will result in reducing the country revenue, threatening the economy and increasing the CO₂ emission. This triggers the alarm for Libya to an urgent plan to diversify the energy sources through using sustainable energy. The sun showers Libya every day by a huge amount of sunshine, especially during the peaks in the summer days. Recently, the country has been struggling to satisfy its escalating energy demands. The residential and street lighting loads constitute more than 50% of the electricity demands in Libya. Street lighting consumes more than 3.996 TW h, which is around one fifth of the energy demands in Libya. Energy conservation and transition from fossil fuel to renewable energy could have significant profit on the energy sector in Libya. For example, Libya is still relying on the old-fashioned, inefficient and unsustainable street lighting systems. Replacing the old technology lighting systems with up-to-date solar powered lighting system can achieve energy saving and sustainability. In this paper, improving the energy situation in Libya through replacing the high pressure sodium street lighting systems with solar powered LED street lighting systems is investigated. A four km road is chosen as a case study. Four alternatives are analyzed; grid-powered high pressure sodium lamp street lighting system, grid-powered LED lamp street lighting system, stand-alone solar powered LED street lighting system and grid-connected solar powered LED street lighting system. The four options are compared in terms of the capital cost, maintenance cost, total cost, fuel cost and the CO₂ emission. Replacing the high pressure sodium lamp system with LED lamp system saves 75% of energy and reduces the CO₂ emission by 75%. The stand-alone solar powered LED lighting system cuts the CO₂ emission, saves the fuel and is economically feasible. Furthermore, improvement is attained if the solar powered lighting system is connected to the grid where the excess energy is fed to the grid. The two solar powered options are economically feasible and sustainable.     

Nonlocal thermoelastic model for temperature-dependent thermal conductivity nanobeams due to dynamic varying loads

Microsystem Technologies - The present paper produces a new nonlocal model for thermoelastic nanobeams of temperature-dependent thermal conductivity. A nanobeam excited by harmonically varying heat...     

Thermophoresis and MHD mixed convection three-dimensional flow of viscoelastic fluid with Soret and Dufour effects

Heat and mass transfer effects in three-dimensional mixed convection flow of viscoelastic fluid over a stretching surface with convective boundary conditions are investigated. The fluid is electrically conducting in the presence of constant applied magnetic field. Conservation laws of energy and concentration are based upon the Soret and Dufour effects. First order chemical reaction effects are also taken into account. By using the similarity transformations, the governing boundary layer equations are reduced into the ordinary differential equations. The transformed boundary layer equations are computed for the series solutions. Dimensionless velocity, temperature, and concentration distributions are shown graphically for different values of involved parameters. Numerical values of local Nusselt and Sherwood numbers are computed and analyzed. It is found that the behaviors of viscoelastic, mixed convection, and concentration buoyancy parameters on the Nusselt and Sherwood numbers are similar. However, the Nusselt and Sherwood numbers have qualitative opposite effects for Biot number, thermophoretic parameter, and Soret-Dufour parameters.

     

Desorption kinetics of trichloroethylene and perchloroethylene from aged dense nonaqueous phase liquid-contaminated soil

Batch experiments were conducted to investigate the desorption kinetics of a contaminated soil collected from a field site at Hill Air Force Base (AFB), Utah. The site has been contaminated with many dense nonaqueous phase liquids (DNAPLs), primarily trichloroethylene (TCE) and perchloroethylene (PCE), for more than 60 years. Similar desorptive behaviour of both TCE and PCE was observed: a stage of fast release of the contaminant at the start followed by a very slow stage. Moreover, it is suggested that not all the contaminant in the solid phase may be released to the aqueous phase, apparently due to the age factor. Local variations were observed in the effective diffusivity and other sorption-related parameters across the site due to aquifer heterogeneity. Experimental results were then simulated using a numerical code based on the intraparticle diffusion model. Good agreement was found between both results.     

The 12<Superscript>th</Superscript> World Conference on Titanium presents research and applications of “wonder metal”

The International Conference on Titanium was begun in 1968 to assess the national significance attached to the development of titanium in relation to the technical needs of the participating countries. The conference, held every four years, attracts strong international participation. This article reviews the 12^th World Conference on Titanium, hosted by the Nonferrous Society of China and held in Beijing, China, 19–24 June 2011.     

Classifying Construction Contractors Using Unsupervised-Learning Neural Networks

Contractor prequalification involves the screening of contractors by a project owner to determine their competence to complete the project on time, within budget, and to expected quality standards. The process of prequalification involves a large number of contractors, each being represented by many attributes. A neural network model was applied to aid in the prequalification process by classifying contractors into groups based on similarity in performance using the financial ratios of liquidity, activity, profitability, and leverage. Contractors are represented in this model by patterns in four-dimensional space. Patterns of similar performance tend to form clusters intercepting regions of low pattern density in between. A neuron with weights is used as a classifier to set a decision boundary between clusters. The method basically iterates the neuron weights to move the decision boundary to a place of low pattern density. Then, the statistical hypothesis testing of the mean difference of two independent samples was used to validate the classification of the parent class to the two child classes considering the four ratios separately. The method was used hierarchically to classify a group of 245 contractors into classes of small numbers. Finally, the inferred procedure of classification proves that the neural network model classified the four-dimension pattern representing contractors efficiently.