Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in controlling and optimizing RAN functions has not been widely investigated. In this paper, we jointly optimize the flow-split distribution, congestion control and scheduling (JFCS) to enable an intelligent traffic steering application in O-RAN. Combining tools from network utility maximization and stochastic optimization, we introduce a multi-layer optimization framework that provides fast convergence, long-term utility-optimality and significant delay reduction compared to the state-of-the-art and baseline RAN approaches. Our main contributions are three-fold: i) we propose the novel JFCS framework to efficiently and adaptively direct traffic to appropriate radio units; ii) we develop low-complexity algorithms based on the reinforcement learning, inner approximation and bisection search methods to effectively solve the JFCS problem in different time scales; and iii) the rigorous theoretical performance results are analyzed to show that there exists a scaling factor to improve the tradeoff between delay and utility-optimization. Collectively, the insights in this work will open the door towards fully automated networks with enhanced control and flexibility. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms in terms of the convergence rate, long-term utility-optimality and delay reduction.Comment: 15 pages, 10 figures. A short version will be submitted to IEEE GLOBECOM 202

Label driven Knowledge Distillation for Federated Learning with non-IID Data

In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an environment with heterogeneous data. Realizing the first problem, we aim to design a novel FL framework named Full-stack FL (F2L). More specifically, F2L utilizes a hierarchical network architecture, making extending the FL network accessible without reconstructing the whole network system. Moreover, leveraging the advantages of hierarchical network design, we propose a new label-driven knowledge distillation (LKD) technique at the global server to address the second problem. As opposed to current knowledge distillation techniques, LKD is capable of training a student model, which consists of good knowledge from all teachers' models. Therefore, our proposed algorithm can effectively extract the knowledge of the regions' data distribution (i.e., the regional aggregated models) to reduce the divergence between clients' models when operating under the FL system with non-independent identically distributed data. Extensive experiment results reveal that: (i) our F2L method can significantly improve the overall FL efficiency in all global distillations, and (ii) F2L rapidly achieves convergence as global distillation stages occur instead of increasing on each communication cycle.Comment: 28 pages, 5 figures, 10 table

Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers

© 2018, King Fahd University of Petroleum & Minerals. Falls represent a major problem for the elderly people aged 60 or above. There are many monitoring systems which are currently available to detect the fall. However, there is a great need to propose a system which is of optimal effectiveness. In this paper, we propose to develop a low-cost fall detection system to precisely detect an event when an elderly person accidentally falls. The fall detection algorithm compares the acceleration with lower fall threshold and upper fall threshold values to accurately detect a fall event. The post-fall recognition module is the combination of posture recognition and vertical velocity estimation that has been added to our proposed method to enhance the performance and accuracy. In case of a fall, our device will transmit the location information to the contacts instantly via SMS and voice call. A smartphone application will ensure that the notifications are delivered to the elderly person’s relatives so that medical attention can be provided with minimal delay. The system was tested by volunteers and achieved 100% sensitivity and accuracy. This was confirmed by testing with public datasets and it also achieved the same percentage in sensitivity and accuracy as in our recorded datasets

Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework

peer reviewedTo enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and development of open RAN (O-RAN). So far, however, the applicability of O-RAN in controlling and optimizing RAN functions has not been widely investigated. In this paper, we jointly optimize the flow-split distribution, congestion control and scheduling (JFCS) to enable an intelligent traffic steering application in O-RAN. Combining tools from network utility maximization and stochastic optimization, we introduce a multi-layer optimization framework that provides fast convergence, long-term utility-optimality and significant delay reduction compared to the state-of-the-art and baseline RAN approaches. Our main contributions are three-fold: i ) we propose the novel JFCS framework to efficiently and adaptively direct traffic to appropriate radio units; ii ) we develop low-complexity algorithms based on the reinforcement learning, inner approximation and bisection search methods to effectively solve the JFCS problem in different time scales; and iii ) the rigorous theoretical performance results are analyzed to show that there exists a scaling factor to improve the tradeoff between delay and utility-optimization. Collectively, the insights in this work will open the door towards fully automated networks with enhanced control and flexibility. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms in terms of the convergence rate, long-term utility-optimality and delay reduction

SWIPT-enabled cooperative wireless IoT networks with friendly jammer and eavesdropper: Outage and intercept probability analysis

Physical layer security (PLS) and simultaneous wireless information and power transfer (SWIPT) in cooperative relaying have gained great interest as technologies for security and energy enhance ment in Internet-of-Things (IoT) networks. In this work, we investigate PLS for a SWIPT- and AF-enabled cooperative wireless IoT system, consisting of one source, multiple energy harvesting (EH) relays, and one destination, in the presence of an eavesdropper that tries to overhear the confidential information. Furthermore, an EH-friendly jammer is deployed to transmit jamming signals aimed at the eavesdropper to improve the security system. In this context, a low-complexity, sub-optimal, but efficient relay selection method is proposed. More specifically, the relay is selected to convey information such that it has the best channel to the source. Based on the proposed system model, the performance analysis of the intercept probability (IP), asymptotic IP, and non-zero secrecy probability (NZSP) is analyzed by considering the time switching (TS)-based relaying strategy. Particularly, the exact closed-form expression of IP is achieved by applying modified Bessel function expansion. Monte-Carlo simulations are employed to corroborate the correctness and efficiency of our mathematical analysis. The time splitting factor α makes variations on the IP of about 3× as α ∈ [0.1, 0.8]. However, a dramatic reduction of the IP up to 317× is observed as α increases from 0.8 to 0.9.Web of Science11861778616

Outage Performance of Satellite Terrestrial Full-DuplexRelaying Networks with Co-Channel Interference

This letter investigates the performance of thesatellite-terrestrial networks (STN), where a satellite tries totransmit information to a ground user through the help of mul-tiple decode-and-forward relays and the existence of co-channelinterference sources. In particular, the full-duplex technique andpartial relay selection are applied at the relay to increase the totalthroughput at the destination, enhance the system reliability, andreduce the complexity. In this context, the outage probability (OP)is computed in a closed-form expression. Numerical results areprovided to confirm the accuracy of the proposed mathematicalframework. Our findings illustrate that the outage performancecan be effectively enhanced by increasing either number of relaysor transmit power

The impact of albendazole treatment on the incidence of viral- and bacterial-induced diarrhea in school children in southern Vietnam: study protocol for a randomized controlled trial

Anthelmintics are one of the more commonly available classes of drugs to treat infections by parasitic helminths (especially nematodes) in the human intestinal tract. As a result of their cost-effectiveness, mass school-based deworming programs are becoming routine practice in developing countries. However, experimental and clinical evidence suggests that anthelmintic treatments may increase susceptibility to other gastrointestinal infections caused by bacteria, viruses, or protozoa. Hypothesizing that anthelmintics may increase diarrheal infections in treated children, we aim to evaluate the impact of anthelmintics on the incidence of diarrheal disease caused by viral and bacterial pathogens in school children in southern Vietnam.This is a randomized, double-blinded, placebo-controlled trial to investigate the effects of albendazole treatment versus placebo on the incidence of viral- and bacterial-induced diarrhea in 350 helminth-infected and 350 helminth-uninfected Vietnamese school children aged 6-15 years. Four hundred milligrams of albendazole, or placebo treatment will be administered once every 3 months for 12 months. At the end of 12 months, all participants will receive albendazole treatment. The primary endpoint of this study is the incidence of diarrheal disease assessed by 12 months of weekly active and passive case surveillance. Secondary endpoints include the prevalence and intensities of helminth, viral, and bacterial infections, alterations in host immunity and the gut microbiota with helminth and pathogen clearance, changes in mean z scores of body weight indices over time, and the number and severity of adverse events.In order to reduce helminth burdens, anthelmintics are being routinely administered to children in developing countries. However, the effects of anthelmintic treatment on susceptibility to other diseases, including diarrheal pathogens, remain unknown. It is important to monitor for unintended consequences of drug treatments in co-infected populations. In this trial, we will examine how anthelmintic treatment impacts host susceptibility to diarrheal infections, with the aim of informing deworming programs of any indirect effects of mass anthelmintic administrations on co-infecting enteric pathogens.ClinicalTrials.gov: NCT02597556 . Registered on 3 November 2015

Security–reliability analysis of AF full-duplex relay networks using self-energy recycling and deep neural networks

This paper investigates the security-reliability of simultaneous wireless information and power transfer (SWIPT)-assisted amplify-and-forward (AF) full-duplex (FD) relay networks. In practice, an AF-FD relay harvests energy from the source (S) using the power-splitting (PS) protocol. We propose an analysis of the related reliability and security by deriving closed-form formulas for outage probability (OP) and intercept probability (IP). The next contribution of this research is an asymptotic analysis of OP and IP, which was generated to obtain more insight into important system parameters. We validate the analytical formulas and analyze the impact on the key system parameters using Monte Carlo simulations. Finally, we propose a deep learning network (DNN) with minimal computation complexity and great accuracy for OP and IP predictions. The effects of the system’s primary parameters on OP and IP are examined and described, along with the numerical data.Web of Science2317art. no. 761

Comparison of accuracy of breeding value for cow from three methods in Hanwoo (Korean cattle) population

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were −0.74 in CWT, −0.75 in EMA, −0.73 in MS, and −0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV

HIV-Associated TB in An Giang Province, Vietnam, 2001–2004: Epidemiology and TB Treatment Outcomes

BACKGROUND: Mortality is high in HIV-infected TB patients, but few studies from Southeast Asia have documented the benefits of interventions, such as co-trimoxazole (CTX), in reducing mortality during TB treatment. To help guide policy in Vietnam, we studied the epidemiology of HIV-associated TB in one province and examined factors associated with outcomes, including the impact of CTX use. METHODOLOGY/PRINCIPAL FINDINGS: We retrospectively abstracted data for all HIV-infected persons diagnosed with TB from 2001-2004 in An Giang, a province in southern Vietnam in which TB patients receive HIV counseling and testing. We used standard WHO definitions to classify TB treatment outcomes. We conducted multivariate analysis to identify risk factors for the composite outcome of death, default, or treatment failure during TB treatment. From 2001-2004, 637 HIV-infected TB patients were diagnosed in An Giang. Of these, 501 (79%) were male, 321 (50%) were aged 25-34 years, and the most common self-reported HIV risk factor was sex with a commercial sex worker in 221 (35%). TB was classified as smear-positive in 531 (83%). During TB treatment, 167 (26%) patients died, 9 (1%) defaulted, and 6 (1%) failed treatment. Of 454 patients who took CTX, 116 (26%) had an unsuccessful outcome compared with 33 (70%) of 47 patients who did not take CTX (relative risk, 0.4; 95% confidence interval [CI], 0.3-0.5). Adjusting for male sex, rural residence, TB smear status and disease location, and the occurrence of adverse events during TB treatment in multivariate analysis, the benefit of CTX persisted (adjusted odds ratio for unsuccessful outcome 0.1; CI, 0.1-0.3). CONCLUSIONS/SIGNIFICANCE: In An Giang, Vietnam, HIV-associated TB was associated with poor TB treatment outcomes. Outcomes were significantly better in those taking CTX. This finding suggests that Vietnam should consider applying WHO recommendations to prescribe CTX to all HIV-infected TB patients