Efficient Virtual Network Function Placement Strategies for Cloud Radio Access Networks

The new generation of 5G mobile services places stringent requirements for cellular network operators in terms of latency and costs. The latest trend in radio access networks (RANs) is to pool the baseband units (BBUs) of multiple radio base stations and to install them in a centralized infrastructure, such as a cloud, for statistical multiplexing gains. The technology is known as Cloud Radio Access Network (CRAN). Since cloud computing is gaining significant traction and virtualized data centers are becoming popular as a cost-effective infrastructure in the telecommunication industry, CRAN is being heralded as a candidate technology to meet the expectations of radio access networks for 5G. In CRANs, low energy base stations (BSs) are deployed over a small geographical location and are connected to a cloud via finite capacity backhaul links. Baseband processing unit (BBU) functions are implemented on the virtual machines (VMs) in the cloud over commodity hardware. Such functions, built-in software, are termed as virtual functions (VFs). The optimized placement of VFs is necessary to reduce the total delays and minimize the overall costs to operate CRANs. Our study considers the problem of optimal VF placement over distributed virtual resources spread across multiple clouds, creating a centralized BBU cloud. We propose a combinatorial optimization model and the use of two heuristic approaches, which are, branch-and-bound (BnB) and simulated annealing (SA) for the proposed optimal placement. In addition, we propose enhancements to the standard BnB heuristic and compare the results with standard BnB and SA approaches. The proposed enhancements improve the quality of the solution in terms of latency and cost as well as reduce the execution complexity significantly.Comment: E-preprin

Reactive Security for SDN/NFV-enabled Industrial Networks leveraging Service Function Chaining

The innovative application of 5G core technologies, namely Software Defined Networking (SDN) and Network Function Virtualization (NFV), can help reduce capital and operational expenditures in industrial networks. Nevertheless, SDN expands the attack surface of the communication infrastructure, thus necessitating the introduction of additional security mechanisms. These major changes could not leave the industrial environment unaffected, with smart industrial deployments gradually becoming a reality; a trend that is often referred to as the 4th industrial revolution or Industry 4.0. A wind park is a good example of an industrial application relying on a network with strict performance, security, and reliability requirements, and was chosen as a representative example of industrial systems. This work highlights the benefit of leveraging the flexibility of SDN/NFV-enabled networks to deploy enhanced, reactive security mechanisms for the protection of the industrial network, via the use of Service Function Chaining. Moreover, the implementation of a proof-of-concept reactive security framework for an industrial-grade wind park network is presented, along with a performance evaluation of the proposed approach. The framework is equipped with SDN and Supervisory Control and Data Acquisition (SCADA) honeypots, modelled on and deployable to the wind park, allowing continuous monitoring of the industrial network and detailed analysis of potential attacks, thus isolating attackers and enabling the assessment of their level of sophistication. Moreover, the applicability of the proposed solutions is assessed in the context of the specific industrial application, based on the analysis of the network characteristics and requirements of an actual, operating wind park

A rare case of omental torsion - a surprise diagnosis of acute pelvic pain

Omental torsion is a rare cause of acute abdominal or pelvic pain. It is rarely diagnosed pre-operatively. It poses a great challenge as it closely mimics the other conditions causing acute surgical abdomen, such as appendicitis, ovarian torsion, ruptured ovarian cyst or ectopic pregnancy etc. Hence, often it presents as a surprise intra-operative diagnosis. Though exploratory laparotomy represents the diagnostic and definitive therapeutic procedure, presently Laparoscopy is the first choice procedure

PHOTOCATALYTIC DEGRADATION OF PHARMACEUTICAL DRUG ZIDOVUDINE BY UNDOPED AND 5 % BARIUM DOPED ZINC OXIDE NANOPARTICLES DURING WATER TREATMENT: SYNTHESIS AND CHARACTERISATION

Objective: To study the photocatalytic degradation of pharmaceutical drug zidovudine (ZDV) by synthesized undoped zinc oxide nanoparticles (ZONPs) and 5% (mole ratio) barium doped zinc oxide nanoparticles (BZONPs) during water treatment.Methods: Kinetics studies were carried out with the help of UV-Visible Spectrophotometer. High-Resolution Mass Spectrophotometry (HR-MS) was used to identify products. A photo-reactor with mercury lamp was used as an external source of light energy. Optical power meter was used for the measurement of light intensity. The particle size of the synthesized photocatalysts was identified with the help of siemens x-ray diffractometer (XRD). The surface topography of photocatalysts was done by scanning electron microscope (SEM). Transmission electron microscopy (TEM) was used for the studies of particle size and morphology.Results: Five degraded products of ZDV are identified by HR-MS. A suitable electron-hole pair mechanism is projected. XRD patterns show that the intensity of peak is slightly stronger in ZONPs. There is an increase in the rate of photocatalytic degradation of ZDV by adding different quantities of photocatalyst from 0.05 g l-1 to 0.1 g l-1. The kinetic data reveals that there is an initial increase in the values of rate constants with the increase in the concentration of ZDV. The kinetic data indicate that the values of rate constants are higher at pH = 9. There is an increase in the rate constant values with an increase in the light intensities of UV lamp.Conclusion: The rates of photocatalytic degradation of ZDV were found to be higher using 5 % (mole ratio) BZONPs as a photocatalyst.Â

In vitro anticancer potential of Manilkara hexandra (Roxb.) leaf methanolic extracts via SRB and MTT assays against MCF-7 cell line

Background: Cancer causes millions of deaths worldwide, with cases expected to reach 28.4 million by 2040. Natural plant compounds offer safer alternatives for cancer treatment. Aim: This study tested the anticancer activity of Manilkara hexandra leaf extracts against MCF-7 breast cancer cells. Materials and methods: Methanolic extraction, followed by sequential fractionation via column chromatography, yielded bioactive fractions that underwent phytochemical and GC-MS characterization. Quantification of cytotoxicity was performed using sulforhodamine B (SRB) and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays across a concentration gradient (10–80 μg/mL). Result and Discussion: Chemical screening found alkaloids, flavonoids, tannins, and other bioactive compounds. The petroleum ether-ethyl acetate (PE-EA) fraction contained quercetin (25.28%) and another major flavonoid (28.62%). This fraction exhibited strong dose-dependent cell killing, reducing cell survival to 31.8% (SRB) and 33.0% (MTT) at 80 μg/mL (p < 0.001). The IC₅₀ was 55 μg/mL in both assays. Conclusion: The anticancer activity correlates with high flavonoid content, suggesting these compounds cause cell death through apoptosis or cell cycle arrest. M. hexandra PE-EA fraction shows promise as a natural anticancer agent for breast cancer treatmen

CERTAIN SUBCLASSES OF P-VALENT MEROMORPHIC CONVEX FUNCTIONS ASSOCIATED WITH MOSTAFA OPERATOR

In this paper we study certain subclasses of analytic p-valent meromorphic convex functions with positive coefficients in the puncture unit disk. The result presented coefficient estimate, growth and distortion properties for functions belonging to this subclasses. Further results of modified hadamard product, inclusion properties, radii of close-to-convexity; starlikeness and convexity for functions belonging to the subclasses are discussed. Keywords: p-Valent meromorphic functions, convex function, Modified Hadamard product, inclusion properties and radii of starlikeness. AMS Subject Classification: 30C4

High strain-rate material model validation for laser peening simulation

Finite element modeling can be a powerful tool for predicting residual stresses induced by laser peening; however the sign and magnitude of the stress predictions depend strongly on how the material model captures the high strain rate response. Although a Johnson-Cook formulation is often employed, its suitability for modeling phenomena at very high strain rates has not been rigorously evaluated. In this paper, we address the effectiveness of the Johnson-Cook model, with parameters developed from lower strain rate material data (∼10^3 s^–1), to capture the higher strain rate response (∼10^5–10^6 s^–1) encountered during the laser peening process. Published Johnson-Cook parameters extracted from split Hopkinson bar testing were used to predict the shock response of aluminum samples during high-impact flyer plate tests. Additional quasi-static and split Hopkinson bar tests were also conducted to study the model response in the lower strain rate regime. The overall objective of the research was to ascertain whether a material model based on conventional test data (quasi-static compression testing and split Hopkinson bar measurements) can credibly be used in FE simulations to predict laser peen-induced stresses

The P-ART framework for placement of virtual network services in a multi-cloud environment

Carriers network services are distributed, dynamic, and investment intensive. Deploying them as virtual network services (VNS) brings the promise of low-cost agile deployments, which reduce time to market new services. If these virtual services are hosted dynamically over multiple clouds, greater flexibility in optimizing performance and cost can be achieved. On the flip side, when orchestrated over multiple clouds, the stringent performance norms for carrier services become difficult to meet, necessitating novel and innovative placement strategies. In selecting the appropriate combination of clouds for placement, it is important to look ahead and visualize the environment that will exist at the time a virtual network service is actually activated. This serves multiple purposes clouds can be selected to optimize the cost, the chosen performance parameters can be kept within the defined limits, and the speed of placement can be increased. In this paper, we propose the P-ART (Predictive-Adaptive Real Time) framework that relies on predictive-deductive features to achieve these objectives. With so much riding on predictions, we include in our framework a novel concept-drift compensation technique to make the predictions closer to reality by taking care of long-term traffic variations. At the same time, near real-time update of the prediction models takes care of sudden short-term variations. These predictions are then used by a new randomized placement heuristic that carries out a fast cloud selection using a least-cost latency-constrained policy. An empirical analysis carried out using datasets from a queuing-theoretic model and also through implementation on CloudLab, proves the effectiveness of the P-ART framework. The placement system works fast, placing thousands of functions in a sub-minute time frame with a high acceptance ratio, making it suitable for dynamic placement. We expect the framework to be an important step in making the deployment of carrier-grade VNS on multi-cloud systems, using network function virtualization (NFV), a reality.This publication was made possible by NPRP grant # 8-634-1-131 from the Qatar National Research Fund (a member of Qatar Foundation), National Science Foundation, USA � CNS-1718929 and National Science Foundation, USA � CNS-1547380 .Scopu