Machine learning based heuristic BBU-RRH switching scheme for C-RAN in 5G

The immense increase in bandwidth demand by various services such as high definition video streaming, online gaming, and virtual reality has made it increasingly challenging for operators to provide satisfactory services to the end users while making a profit. Cloud Radio Access Network (C-RAN) is a new architecture that has been proposed to facilitate the mobile networks' ability to meet the increase in bandwidth demand. C-RAN consists of three parts, namely Remote Radio Head (RRH), the front haul link, and Baseband Processing Units (BBU) pool. Many RRHs are associated with one BBU pool, and all RRHs within the pool are logically connected to every BBU in the pool. Thus, a BBU-RRH switching algorithm needs to be developed as it is able to enhance the performance of such architecture while managing the resource efficiently. This work mainly focuses on developing a traffic profile prediction-based BBU-RRH switching algorithm using a real life dataset. In the literature, there are related works that have proposed algorithms to achieve this purpose. However some of the existing algorithms suffer from high switching complexity while others fall short in QoS provision. Therefore, this work develops a BBU-RRH algorithm that to enhance the QoS while reducing the switching complexity, with the aid of machine learning techniques. The algorithm developed consists of three parts. The first part consists of an efficient RRH clustering mechanism that determines which RRHs are associated with a specific BBU pool. The second part utilizesrecurrent neural networks (RNN) to predict the daily traffic profile of RRHs, so that a relatively accurate traffic profile prediction can be obtained to facilitate the switching algorithm. Finally, the third part comprises the BBU-RRH switching scheme that works in conjunction with the predicted traffic profile to make an informed decision about the associations between RRHs and BBUs within the BBU pool. The performance of the proposed algorithm has been evaluated through simulations. The simulation results show that the proposed algorithm reduces the number of BBUs used and therefore save on energy. In addition, the algorithm reduces the occurrence of congestion and failure states, and thus improve the quality of the service of the network. Finally, the developed switching algorithm also reduces the switching complexity when compared with existing algorithms

Dynamic Response Analysis of Ash-Retention Dam and Its Earthquake-Resistant Improvement

A nonlinear stress-strain static evaluation model and an equivalent visco-elastic dynamic evaluation model, which can simulate well the static and seismic behaviors of the ash deposit, as well as the methods for analyzing the dynamic response and for improving the earthquake-resistance of the ash-retention dam are presented and illustrated through a practical engineering project in the paper

Traffic-Profile and Machine Learning Based Regional Data Center Design and Operation for 5G Network

Data center in the fifth generation (5G) network will serve as a facilitator to move the wireless communication industry from a proprietary hardware based approach to a more software oriented environment. Techniques such as Software defined networking (SDN) and network function virtualization (NFV) would be able to deploy network functionalities such as service and packet gateways as software. These virtual functionalities however would require computational power from data centers. Therefore, these data centers need to be properly placed and carefully designed based on the volume of traffic they are meant to serve. In this work, we first divide the city of Milan, Italy into different zones using K-means clustering algorithm. We then analyse the traffic profiles of these zones in the city using a network operator’s Open Big Data set. We identify the optimal placement of data centers as a facility location problem and propose the use of Weiszfeld’s algorithm to solve it. Furthermore, based on our analysis of traffic profiles in different zones, we heuristically determine the ideal dimension of the data center in each zone. Additionally, to aid operation and facilitate dynamic utilization of data center resources, we use the state of the art recurrent neural network models to predict the future traffic demands according to past demand profiles of each area

Research on flux of dry atmospheric falling dust and its characterization in a subtropical city, Guangzhou, South China

Guangzhou is the central city in the Pearl River Delta (PRD), China, and is one of the most polluted cities in the world. To characterize the ambient falling dust pollution, two typical sampling sites: urban (Wushan) and suburban (University Town) areas in Guangzhou city were chosen for falling dust collection over 1 year at time intervals of 1 or 2 months. The flux of dry deposition was calculated. In addition, mineral composition and morphology of atmospheric falling dust were studied by X-ray diffraction, scanning electron microscopy, and microscopic observation. The results revealed that the dust flux in Guangzhou city was 3.34–3.78 g/(m2 month) during the study period. The main minerals in the dust were quartz, illite, calcite, kaolinite, gypsum, plagioclase, dolomite, and amorphous matter. The morphological types included grained and flaky individual minerals, chain-like aggregates, spherical flying beads, and irregular aggregates, with the chain-like and spherical aggregates indicators of industrial ash. The major dusts were derived from industrial and construction activities. The gypsum present in the dust collected in winter season was not only derived from cement dust but may also have originated from the reaction of calcic material with sulfuric acids resulting from photooxidation of SOx and NOx, which confirmed serious air pollution due to SOx and NOx in Guangzhou. The abatement of fossil fuel combustion emissions and construction dust will have a significant beneficial effect on dust reduction

Watching Stars in Pixels: The Interplay of Traffic Shaping and YouTube Streaming QoE over GEO Satellite Networks

Geosynchronous satellite (GEO) networks are a crucial option for users beyond terrestrial connectivity. However, unlike terrestrial networks, GEO networks exhibit high latency and deploy TCP proxies and traffic shapers. The deployment of proxies effectively mitigates the impact of high network latency in GEO networks, while traffic shapers help realize customer-controlled data-saver options that optimize data usage. It is unclear how the interplay between GEO networks' high latency, TCP proxies, and traffic-shaping policies affects the quality of experience (QoE) for commonly used video applications. To fill this gap, we analyze the quality of over $2$k YouTube video sessions streamed across a production GEO network with a $900$Kbps shaping rate. Given the average bit rates for the selected videos, we expected seamless streaming at $360$p or lower resolutions. However, our analysis reveals that this is not the case: $28\%$ of TCP sessions and $18\%$ of gQUIC sessions experience rebuffering events, while the median average resolution is only $380$p for TCP and $299$p for gQUIC. Our analysis identifies two key factors contributing to sub-optimal performance: (i)unlike TCP, gQUIC only utilizes $63\%$ of network capacity; and (ii)YouTube's imperfect chunk request pipelining. As a result of our study, the partner GEO ISP discontinued support for the low-bandwidth data-saving option in U.S. business and residential markets to avoid potential degradation of video quality -- highlighting the practical significance of our findings

Emission of PAHs, NPAHs and OPAHs from residential honeycomb coal briquette combustion

Coal combustion is one of the most significant sources of air pollution in China. In this study, emission factors (EFs) of 15 polycyclic aromatic hydrocarbons (PAHs), 26 nitrated PAHs (NPAHs) and 6 oxygenated PAHs (OPAHs) were determined in five different coals with different geological maturity (vitrinite reflectance <i>R</i>_O = 0.77–1.88%) burned in the form of honeycomb briquettes. The total EFs ranged from 9.82 to 215 mg kg^–1 for PAHs, 0.14 to 1.88 mg kg^–1 for NPAHs and 4.47 to 20.8 mg kg^–1 for OPAHs. Measured EFs and gas-particle partitioning varied depending on the geological maturity. The lowest EFs were found in anthracite. The proportion of PAHs, NPAHs and OPAHs in gaseous phase increasing with increased geological maturity. The coal with higher geological maturity produced more 3-ring PAHs. On the basis of the statistical analysis for the residential sector of China in 2008, PAHs, NPAHs and OPAHs emitted from residential honeycomb coal briquettes were 4.36 Gg, 0.03 Gg and 0.47 Gg in 2007, respectively. By 2020, the emission would decrease to 2.18 Gg, 0.02 Gg and 0.24 Gg for PAHs, NPAHs and OPAHs due to the increasing usage of new energy resources. If only anthracite is used as the residential coal, 93% PAHs, 87% NPAHs and 71% OPAHs would be reduced in 2020

Full-duplex mode in amplify-and-forward relay channels: outage probability and ergodic capacity

This paper investigates the outage probability and ergodic capacity performances for full-duplex mode in two-way amplify-andforward relay channels. The two-way relay channels which consist of two source nodes and a single relay node working in full-duplex mode, are assumed as independent and identically distributed as Rayleigh fading. The self-interference or loop interference of the relay is unavoidably investigated for full-duplex mode. And the close-form expressions for the outage probability and ergodic capacity of full-duplex mode are derived, considering both loop interference and the coefficients of two-way relay amplify-andforward channels. To further facilitate the performance of full-duplex mode, the half-duplex modes over different transmission time slots are analyzed. Simulation results point out the effect of loop interference on outage probability and ergodic capacity of twoway amplify-and-forward relay channels with full-duplex mode and show that full-duplex mode can achieve better performance in terms of capacity and even outperform half-duplex modes in the presence of loop interference