On the use of prioritization and network slicing features for mission critical and commercial traffic multiplexing in 5G Radio Access Networks

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The Public Protection and Disaster Relief (PPDR) sector is undergoing an important transition with the deployment of Mission Critical (MC) mobile broadband technology based on 3GPP standards, with multiple initiatives on-going worldwide for providing PPDR agencies with broadband communications capabilities. One common approach being adopted is the delivery of MC services together with commercial traffic over public mobile networks and the use of prioritization mechanisms to protect the MC connections in congestion situations. However, this approach leaves commercial traffic unprotected in front of a noncontrolled surge of MC traffic in specific cells since all resources would be allocated to serve this traffic. In this context, this paper proposes a solution to properly multiplex MC and commercial services with congestion protection for both types of services. The solution is based on the exploitation of the network slicing features brought into the new 5G standards. In particular, the paper describes how different slices can be parameterized in a 5G Radio Access Network (RAN) so that radio load guarantees can be established for each type of service. The proposed solution is evaluated in an illustrative scenario by means of simulations. Obtained results show the improvements in traffic isolation achievable by the slicing configuration when compared to the solution that only relies on prioritization mechanismsPeer ReviewedPostprint (author's final draft

Coordination of radio access and optical transport

New 5G and beyond applications demand strict delay requirements. In this paper, we propose coordination between radio access and optical transport to guarantee such delay while optimizing optical capacity allocation. Illustrative results show near real-time autonomous capacity adaptation benefits based on radio access delay requirements.The research leading to these results has received funding from the HORIZON SEASON (G.A. 101096120), the UNICO5G TIMING (TSI-063000-2021-145), and the MICINN IBON (PID2020-114135RB-I00) projects and from the ICREA institution.Peer ReviewedPostprint (author's final draft

Chlorogenic Acid Ameliorates Damage Induced by Fluorene-9-Bisphenol in Porcine Sertoli Cells

4,4′-(9-Fluorenylidene) diphenol (BPFL, also known as BHPF and fluorene-9-bisphenol) is a novel bisphenol A substitute that is used in the plastics industry as an organic synthesis intermediate and is a potential endocrine disruptor. However, the deleterious effects of BPFL on porcine Sertoli cells (SCs) and the possible underlying mechanisms are still unclear. Chlorogenic acid (CA) is a free radical scavenger in the cellular antioxidant system that prevents oxidative damage and apoptosis. In the present research, we found that BPFL induced impairments in porcine SCs in a dose-dependent manner and that CA protected porcine SCs against BPFL exposure-induced impairments. Cell viability, proliferation and apoptosis assay results revealed that BPFL exposure could inhibit porcine SC proliferation and induce apoptosis, while CA supplementation ameliorated the effects of BPFL. Further analysis revealed that BPFL exposure induced oxidative stress, mitochondrial membrane potential dysfunction and DNA damage accumulation. Transcriptome analysis and further real-time quantitative PCR and Western blot results showed that BPFL exposure induced endoplasmic reticulum stress and apoptosis. Supplementation with CA dramatically ameliorated these phenotypes in BPFL-exposed porcine SCs. Overall, the present research reveals the possible underlying mechanisms by which BPFL exposure induced impairments and CA supplementation protected against these impairments in porcine SCs

ULK1/2 Constitute a Bifurcate Node Controlling Glucose Metabolic Fluxes in Addition to Autophagy

揭示了在外界能量供应缺乏时，细胞通过激活ULK1来介导葡萄糖分解代谢重编程以维持胞内的能量与氧化还原稳态的详细机制，并创新地发现了ULK1独立于自噬的关键功能。基于自噬和糖代谢与人类健康的重要相关性，该研究将很可能为我们预防和治疗各类代谢疾病提供新的思路和药物靶点。Metabolic reprogramming is fundamental to biological homeostasis, enabling cells to adjust metabolic routes after sensing altered availability of fuels and growth factors. ULK1 and ULK2 represent key integrators that relay metabolic stress signals to the autophagy machinery. Here, we demonstrate that, during deprivation of amino acid and growth factors, ULK1/2 directly phosphorylate key glycolytic enzymes including hexokinase (HK), phosphofructokinase 1 (PFK1), enolase 1 (ENO1), and the gluconeogenic enzyme fructose-1,6-bisphosphatase (FBP1). Phosphorylation of these enzymes leads to enhanced HK activity to sustain glucose uptake but reduced activity of FBP1 to block the gluconeogenic route and reduced activity of PFK1 and ENO1 to moderate drop of glucose-6-phosphate and to repartition more carbon flux to pentose phosphate pathway (PPP), maintaining cellular energy and redox homeostasis at cellular and organismal levels. These results identify ULK1/2 as a bifurcate-signaling node that sustains glucose metabolic fluxes besides initiation of autophagy in response to nutritional deprivation.State Key Program of National Natural Science of China， the 973 Program；National Natural Science Foundation of China for Fostering Talents in Basic Research ；the Foundation for Innovative Research Groups of the National Natural Science Foundation of China； and the 111 Project of Education of China

Hate Crime Analysis based on Artificial Intelligence Methods

Hate crimes always take a toll on American citizens, which harms social security. It is essential for researchers to explore the factors, which lead to hate crimes. This research is to find out the relationship between hate crimes and factors including income inequality, median household income, race using Machine Learning methods. Machine Learning, as an important branch in Artificial Intelligence, is a good way for finding relationships between things. The research is based on a dataset of hate crimes rates in the 2016 U.S. presidential election as well as hate crimes rates in every U.S. state from 2010 to 2015. Simply linear regression and multiple linear regression are used to describe the factors that influence the crime rate and their contributions, such as share of white poverty or share of non-white residents, or the median household income. Then, K-means is applied to classify hate crimes into 5 levels according to the crime rate. Furthermore, KNearest Neighbors is used to demonstrate a prediction of hate crime. At last, a histogram is applied to indicate the variance of the hate crimes in different states. From linear regression, four highest correlation coefficients with a hate crime can be found out, which are income inequality, median household income, the share of noncitizen, and race in turn. Income inequality has the highest correlation coefficient with a hate crime. From multiple linear regression, it can be found out that only by implementing income inequality, median household income, and race can we obtain the highest R square values, which are 0.44 for 2010 to 2015 hate crimes and 0.33 for 2016 hate crimes. From the K-Nearest Neighbors method, hate crimes can be predicted with an accuracy of 40% by applying median household income. Adding the race factor, accuracy rises to 50%. In summary, income inequality, median household income, and race have a high impact on the crime rate. The median household income and the race could predict the crime rate with an accuracy of about 50%

Adaptive Rendering and Scheduling Techniques to Enable Cloud Mobile Gaming

This dissertation studies a new cloud server based approach for mobile gaming, termed Cloud Mobile Gaming (CMG), that enables 3D, multiplayer, Internet video games on mobile phones -- the kinds of games that today require a powerful PC tethered to the Internet. We flipped the traditional client-server architecture for PC-based Internet games on its head and looked to cloud computing, instead of putting most of the storage and computational burden of the games on the mobile device. Though promising, the new CMG approach will impose other challenges, namely to ensure high mobile gaming user experience (as two-way gaming data including video will need to be transmitted through wireless networks in real time), and ensure scalability in terms of cloud servers and network bandwidth, so as to ensure economic viability of the approach. In our work, we have developed key new technologies to address these challenges. We first developed and validated a Mobile Gaming User Experience model, which can quantitatively measure user perceived mobile gaming experience. Next, we develop an adaptive rendering technique which can simultaneously vary the richness and complexity of graphic rendering to adapt the communication and computing needs of each CMG session in responding to the dynamic conditions of the wireless networks and cloud server. Finally, we present a mobile cloud scheduling approach which can allocate resources to meet user experience requirements while maximizing the number of users which can be scheduled concurrently and minimizing cloud cost. The experimental results presented demonstrate that our proposed adaptive rendering technique and the mobile cloud scheduling approach can efficiently address the challenges imposed by the wireless network and cloud server, ensuring the user perceived gaming quality as well as the scalability for the CMG approach. We believe the techniques proposed in this work will not only enable rich Internet cloud gaming, but also other rich mobile multimedia applications using the clou

Addressing Response Time and Video Quality in Remote Server Based Internet Mobile Gaming

Abstract—A new remote server based gaming approach, where the responsibility of executing the gaming engines is put on remote servers instead of the mobile devices, has the potential for enabling mobile users to play the same rich Internet games available to PC users. However, the mobile gaming user experience may be limited by risks of unacceptably high response time, and low gaming video quality, as gaming control commands, and the resulting gaming video, have to travel through wireless networks characterized by high bandwidth fluctuations, latency and packet loss. In this paper, we propose a set of application layer optimization techniques to ensure acceptable gaming response time and video quality in the remote server based approach. The techniques include downlink gaming video rate adaptation, uplink delay optimization, and client play-out delay adaptation. Experiments conducted on a commercial HSDPA network demonstrate that the proposed optimization techniques can make the remote server based approach feasible, allowing rich Internet games to be played on mobile devices, while ensuring acceptable user experience. devices, as it will eliminate the need for mobile devices to download and execute the memory and computation intensive gaming engines. The Remote Server Based Mobile Gaming (RSBMG) approach, including the associated control and data flows, is shown in Figure 1. It extends the traditional game content server with two additional components: game engine servers and game streaming servers. The mobile user issues a game command on the mobile device, which is delivered to the remote gaming server using the wireless uplink channel, and accepted by the game content server. The game engine server then loads the client’s account information and game data from the content server, and starts to process the game logic and user data to render the raw game video. The generated raw game video is encoded by the game streaming server, and finally sent to the mobile client via the downlink wireless connection. I

Modeling and Characterizing User Experience in a Cloud Server Based Mobile Gaming Approach

Abstract—With the evolution of mobile devices and networks, and the growing trend of mobile Internet access, rich, multi-player gaming using mobile devices, similar to PC-based Internet games, has tremendous potential and interest. However, the current client-server architecture for PC-based Internet games, where most of the storage and computational burden of the game lies with the client device, does not work with mobile devices, constraining mobile gaming to either downloadable, single player games, or very light non-interactive versions of the rich multi-player Internet games. In this paper, we study a cloud server based approach, termed Cloud Mobile Gaming (CMG), where the burden of executing the gaming engines is put on cloud servers, and the mobile devices just communicate the users ’ gaming commands to the servers. We analyze the factors affecting the quality of user experience using the CMG approach, including the game genres, video encoding factors, and the conditions of the wireless network. Based on the above analysis, we develop a model for Mobile Gaming User Experience (MGUE), and develop a prototype for real-time measurement of MGUE that can be used in real networks. We validate MGUE model using controlled subjective testing, and then use it to characterize user experience achievable using the CMG approach in wireless networks. I

Modeling and Characterizing User Experience in a Cloud Server Based Mobile Gaming Approach

Abstract—With the evolution of mobile devices and networks, and the growing trend of mobile Internet access, rich, multi-player gaming using mobile devices, similar to PC-based Internet games, has tremendous potential and interest. However, the current client-server architecture for PC-based Internet games, where most of the storage and computational burden of the game lies with the client device, does not work with mobile devices, constraining mobile gaming to either downloadable, single player games, or very light non-interactive versions of the rich multi-player Internet games. In this paper, we study a cloud server based approach, termed Cloud Mobile Gaming (CMG), where the burden of executing the gaming engines is put on cloud servers, and the mobile devices just communicate the users ’ gaming commands to the servers. We analyze the factors affecting the quality of user experience using the CMG approach, including the game genres, video encoding factors, and the conditions of the wireless network. Based on the above analysis, we develop a model for Mobile Gaming User Experience (MGUE), and develop a prototype for real-time measurement of MGUE that can be used in real networks. We validate MGUE model using controlled subjective testing, and then use it to characterize user experience achievable using the CMG approach in wireless networks. I