• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.107-118
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• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.549-559
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• 2023

As mobile edge computing (MEC) is gaining attention as a core technology of 5G networks, edge AI technology of 5G network environment based on mobile user data is recently being used in various fields. However, as in traditional AI security, there is a possibility of adversarial interference of standard 5G network functions within the core network responsible for edge AI core functions. In addition, research on data poisoning attacks that can occur in the MEC environment of standalone mode defined in 5G standards by 3GPP is currently insufficient compared to existing LTE networks. In this study, we explore the threat model for the MEC environment using NWDAF, a network function that is responsible for the core function of edge AI in 5G, and propose a feature selection method to improve the performance of detecting data poisoning attacks for Leaf NWDAF as some proof of concept. Through the proposed methodology, we achieved a maximum detection rate of 94.9% for Slowloris attack-based data poisoning attacks in NWDAF.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.188-210
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• 2022

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.

• Journal of Food Hygiene and Safety
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• v.29 no.3
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• pp.223-227
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• 2014

This study was investigated to determine the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) isolated from raw milk samples and to further study on the molecular characteristics of the MRSA isolates. Using Staphylococcus Medium 110, Staphylococcus spp. were isolated from raw milk samples and further identification was carried by Vitek2 system. Minimum inhibitory concentrations (MICs) of antibiotics were conducted by serial dilution method according to the Clinical Laboratory Standards Institute (CLSI) guideline. For the detection of resistance genes and molecular characterization, PCR reaction was performed by gene specific primers and followed by DNA sequencing. Of the 698 milk samples, 94 Staphylococcus aureus (S. aureus) were identified (94 S. aureus/286 Staphylococcus spp.). Of the 94 S. aureus, seven isolates have mecA, a methicillin resistant gene. mecA positive seven isolates were then characterized by staphylococcal cassette chromosome mec (SCCmec) typing, and Panton-Valentine Leukocidin (pvl) gene using PCR. All of mecA positive isolates were resistant to ampicillin and oxacillin, but sensitive to teicoplanin, vancomycin and ciprofloxacin. One of seven isolates was SCCmec type II and six isolates were type IV and all seven isolates were pvl gene negative.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.41-49
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• 2023

This study examined the effect of input substrate concentration on hydrogen production of microbial electrolysis cells. To compare the performance of MEC according to the input substrate concentration, six laboratory-scale MEC reactors were operated by sequentially increasing the input substrate concentration from 2 g/L of sodium acetate, to 4 g/L, and 6 g/L. The current density, hydrogen production, and SCOD removal rate were analyzed, and energy efficiency and cathodic hydrogen recovery were calculated to compare the performance of MEC. The maximum volumetric current density was obtained at 4 g/L condition (76.3 A/m³) and it decreased to 19.0 A/m³, when the input concentration was increased to 6 g/L, which was a 75% decrease compared to the 4 g/L input condition. Maximum hydrogen production was obtained also at 4 g/L condition (47.3 ± 16.8 mL), but maximum hydrogen yield was obtained at 2 g/L input condition (1.1 L H₂/g COD_in). Energy efficiencies were also highest in 2 g/L condition; the lowest result was observed at 6 g/L condition. Maximum electrical energy efficiency was 76.4%, and the maximum overall energy efficiency was 39.7% at 2 g/L condition. However, when the substrate concentration increased to 6 g/L, the performance was drastically decreased. Cathodic hydrogen recovery also showed a similar tendency with energy efficiency, with the lowest concentration condition showing the best performance. It can be concluded that operating at low input substrate concentration might be better when considering not only hydrogen yield but also energy efficiency.

• Korean Journal of Veterinary Service
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• v.33 no.3
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• pp.233-240
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• 2010

Methicillin-resistant coagulase-negative staphylococci (MRCNS) were isolated from the respiratory sites of chickens in 4 farms and slaughter house located in Chungnam provinces. Isolation of coagulase-negative staphylococci (CNS) was positive for 61 (26.6%) of the 229 chickens tested, and isolation of MRCNS was positive for 17 (27.9%) of the isolated CNS. A total of 17 MRCNS isolates were selected and subjected to identification. Of the 17 MRCNS isolates selected, 6 were identified as Staphylococcus cohnii, 2 as S. saprophyticus, 3 as S. simulans, 3 as S. lentus, 2 as S. carnosus, and 1 as S. xylosus. The MRCNS isolates were resistant to many beta-lactam antibiotics, and some isolates were also resistant to macrolide and aminoglycoside antibiotics. The mecA gene was detected in some isolates of each MRCNS strains. The mecA-positive isolates were classified into five staphylococcal cassette chromosome mec (SCCmec). SCCmec types I to IV were detected in isolates from chickens.

• Journal of Microbiology and Biotechnology
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• v.17 no.4
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• pp.673-676
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• 2007

A two-step triplex PCR assay targeting the mecA, femA, and nuc genes was developed for the detection of methicillin resistance genes harbored by some Staphylococcus aureus isolates and for the simultaneous identification of such isolates at the species level. The triplex PCR revealed the presence of the femA and nuc genes in all the S. aureus isolates examined (n=105). Forty-four clinical isolates were mecA positive and no foodborne isolates were mecA positive. The PCR results had a 98 or 99% correlation with the results of PBP2a latex agglutination tests or oxacillin susceptibility tests, respectively.

• Journal of Food Hygiene and Safety
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• v.23 no.2
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• pp.121-128
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• 2008

The aim of this study was to develop a LightCycler-based real time PCR (LC-PCR) assay and to evaluate its diagnostic use for the detection of Staphylococcus aureus in raw milk samples. Following amplification of 113 bp of coa gene encoding an coagulase precursor specific for Staphylococcus aureus, melting curve and DNA sequencing analysis was performed to verify the specificity of the PCR products. Amplification of 209 bp gene encoding an altered penicillin-binding protein, PBP2a (mecA), melting curve analysis and DNA sequencing analysis was performed to verify methicillin resistance Staphylococcus aureus (MRSA). According to this study, 6 of 647 raw milk samples showed S. aureus positive and 2 of them showed a mecA positive and the detection limit was 10 fg of DNA. And we also isolated Staphylococcus chromogenes a causative agent of exudative epidermitis in pigs and cattle from 3 samples.

• Biomedical Science Letters
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• v.25 no.1
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• pp.75-82
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• 2019

We developed the multiplex LAMP assay using 16S rRNA, femA and mecA genes for direct detection of the methicillin resistance in Staphylococci from positive blood culture. To simultaneously recognize Staphylococci genus, S. aureus and methicillin resistance, three sets of six primers for 16S rRNA, femA and mecA were designed, respectively. The performance of LAMP assay was affirmed using VITEK system for the phenotypic methods of identification and for oxacillin and cefoxitin antimicrobial susceptibility. The optimal condition for LAMP assay was obtained under $64^{\circ}C$ for 50 min. The detection limit was determined to be of 20 copies and CFU/reaction ($10^4CFU/mL$). For clinical application of comparison with phenotypic methods, the sensitivity and specificity of the LAMP with femA gene for detecting S. aureus was 95.31% and 100%, respectively. The sensitivity and specificity of the LAMP with mecA gene for detecting methicillin resistance was 98.46% and 100%, respectively. The multiplex LAMP assay with femA and mecA gene successfully detected all of MRSA (38 isolates) isolates from 103 Staphylococci in blood cultures. The LAMP assay developed in this study is sensitive, specific, and of excellent agreement with the phenotypic methods.