• Title/Summary/Keyword: short-term QoS

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Opportunistic Scheduling with QoS Constraints for Multiclass Services HSUPA System

  • Liao, Dan;Li, Lemin
    • ETRI Journal
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    • v.29 no.2
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    • pp.201-211
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    • 2007
  • This paper focuses on the scheduling problem with the objective of maximizing system throughput, while guaranteeing long-term quality of service (QoS) constraints for non-realtime data users and short-term QoS constraints for realtime multimedia users in multiclass service high-speed uplink packet access (HSUPA) systems. After studying the feasible rate region for multiclass service HSUPA systems, we formulate this scheduling problem and propose a multi-constraints HSUPA opportunistic scheduling (MHOS) algorithm to solve this problem. The MHOS algorithm selects the optimal subset of users for transmission at each time slot to maximize system throughput, while guaranteeing the different constraints. The selection is made according to channel condition, feasible rate region, and user weights, which are adjusted by stochastic approximation algorithms to guarantee the different QoS constraints at different time scales. Simulation results show that the proposed MHOS algorithm guarantees QoS constraints, and achieves high system throughput.

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An Adaptive Traffic Interference Control System for Wireless Home IoT services (무선 홈 IoT 서비스를 위한 적응형 트래픽 간섭제어 시스템)

  • Lee, Chong-Deuk
    • Journal of Digital Convergence
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    • v.15 no.4
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    • pp.259-266
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    • 2017
  • The massive traffic interferences in the wireless home IoT provides the reason for packet losses, and it degrades the QoS (Quality of Service) and throughput on the home network. This paper propose a new adaptive traffic interference control system, ATICS, for enhancing QoS and throughput for IoT services as detecting a traffic process and non-traffic process in the wireless home network. The proposed system control the traffic interferences as distinguishing the short-term traffic process and long-term traffic process by traffic characteristics in wireless home networks. The simulation results shows that the proposed scheme have more efficient traffic control performance than the other schemes.

Video Quality Assessment Based on Short-Term Memory

  • Fang, Ying;Chen, Weiling;Zhao, Tiesong;Xu, Yiwen;Chen, Jing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2513-2530
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    • 2021
  • With the fast development of information and communication technologies, video streaming services and applications are increasing rapidly. However, the network condition is volatile. In order to provide users with better quality of service, it is necessary to develop an accurate and low-complexity model for Quality of Experience (QoE) prediction of time-varying video. Memory effects refer to the psychological influence factor of historical experience, which can be taken into account to improve the accuracy of QoE evaluation. In this paper, we design subjective experiments to explore the impact of Short-Term Memory (STM) on QoE. The experimental results show that the user's real-time QoE is influenced by the duration of previous viewing experience and the expectations generated by STM. Furthermore, we propose analytical models to determine the relationship between intrinsic video quality, expectation and real-time QoE. The proposed models have better performance for real-time QoE prediction when the video is transmitted in a fluctuate network. The models are capable of providing more accurate guidance for improving the quality of video streaming services.

Price-Based Quality-of-Service Control Framework for Two-Class Network Services

  • Kim, Whan-Seon
    • Journal of Communications and Networks
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    • v.9 no.3
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    • pp.319-329
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    • 2007
  • This paper presents a price-based quality-of-service (QoS) control framework for two-class network services, in which circuit-switched and packet-switched services are defined as "premium service class" and "best-effort service class," respectively. Given the service model, a customer may decide to use the other class as a perfect or an imperfect substitute when he or she perceives the higher utility of the class. Given the framework, fixed-point problems are solved numerically to investigate how static pricing can be used to control the demand and the QoS of each class. The rationale behind this is as follows: For a network service provider to determine the optimal prices that maximize its total revenue, the interactions between the QoS-dependent demand and the demand-dependent QoS should be thoroughly analyzed. To test the robustness of the proposed model, simulations were performed with gradually increasing customer demands or network workloads. The simulation results show that even with substantial demands or workloads, self-adjustment mechanism of the model works and it is feasible to obtain fixed points in equilibrium. This paper also presents a numerical example of guaranteeing the QoS statistically in the short term-that is, through the implementation of pricing strategies.

Quality of Life in Older Adults with Cochlear Implantation: Can It Be Equal to That of Healthy Older Adults?

  • Tokat, Taskin;Muderris, Togay;Bozkurt, Ergul Basaran;Ergun, Ugurtan;Aysel, Abdulhalim;Catli, Tolgahan
    • Korean Journal of Audiology
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    • v.25 no.3
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    • pp.138-145
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    • 2021
  • Background and Objectives: This study aimed to evaluate the audiologic results after cochlear implantation (CI) in older patients and the degree of improvement in their quality of life (QoL). Subjects and Methods: Patients over 65 years old who underwent CI at implant center in Bozyaka Training and Research Hospital were included in this study (n=54; 34 males and 20 females). The control group was patient over 65 years old with normal hearing (n=54; 34 males and 20 females). We administered three questionnaires [World Health Organization Quality of Life-BREF (WHOQOL-BREF), World Health Organization Quality of Life-OLD (WHOQOL-OLD)], and Geriatric Depression Scale (GDS) to evaluate the QoL, CIrelated effects on activities of daily life, and social activities in all the subjects. Moreover, correlations between speech recognition and the QoL scores were evaluated. The duration of implant use and comorbidities were also examined as potential factors affecting QoL. Results: The patients had remarkable improvements (the mean score of postoperative speech perception 75.7%) in speech perception after CI. The scores for the WHOQOL-OLD and WHOQOL-BREF questionnaire responses were similar in both the study and control groups, except those for a two subdomains (social relations and social participation). The patients with longer-term CI had higher scores than those with short-term CI use. In general, the changes in GDS scores were not significant (p<0.05). Conclusions: The treatment of hearing loss with CI conferred significant improvement in patient's QoL (p<0.01). The evaluation of QoL can provide multidimensional insights into a geriatric patient's progress and, therefore, should be considered by audiologists.

Quality of Life in Older Adults with Cochlear Implantation: Can It Be Equal to That of Healthy Older Adults?

  • Tokat, Taskin;Muderris, Togay;Bozkurt, Ergul Basaran;Ergun, Ugurtan;Aysel, Abdulhalim;Catli, Tolgahan
    • Journal of Audiology & Otology
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    • v.25 no.3
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    • pp.138-145
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    • 2021
  • Background and Objectives: This study aimed to evaluate the audiologic results after cochlear implantation (CI) in older patients and the degree of improvement in their quality of life (QoL). Subjects and Methods: Patients over 65 years old who underwent CI at implant center in Bozyaka Training and Research Hospital were included in this study (n=54; 34 males and 20 females). The control group was patient over 65 years old with normal hearing (n=54; 34 males and 20 females). We administered three questionnaires [World Health Organization Quality of Life-BREF (WHOQOL-BREF), World Health Organization Quality of Life-OLD (WHOQOL-OLD)], and Geriatric Depression Scale (GDS) to evaluate the QoL, CIrelated effects on activities of daily life, and social activities in all the subjects. Moreover, correlations between speech recognition and the QoL scores were evaluated. The duration of implant use and comorbidities were also examined as potential factors affecting QoL. Results: The patients had remarkable improvements (the mean score of postoperative speech perception 75.7%) in speech perception after CI. The scores for the WHOQOL-OLD and WHOQOL-BREF questionnaire responses were similar in both the study and control groups, except those for a two subdomains (social relations and social participation). The patients with longer-term CI had higher scores than those with short-term CI use. In general, the changes in GDS scores were not significant (p<0.05). Conclusions: The treatment of hearing loss with CI conferred significant improvement in patient's QoL (p<0.01). The evaluation of QoL can provide multidimensional insights into a geriatric patient's progress and, therefore, should be considered by audiologists.

A Deep Learning Model for Extracting Consumer Sentiments using Recurrent Neural Network Techniques

  • Ranjan, Roop;Daniel, AK
    • International Journal of Computer Science & Network Security
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    • v.21 no.8
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    • pp.238-246
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    • 2021
  • The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

Meta-analysis of the Efficacy of Infliximab in Patients with Moderate-Severe Ulcerative Colitis (중등도-중증 궤양성 대장염 환자에서 infliximab의 치료효과에 대한 메타분석)

  • Kim, Jong Yoon;Lee, Sukhyang;Rhew, Ki Yon
    • Korean Journal of Clinical Pharmacy
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    • v.22 no.3
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    • pp.251-259
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    • 2012
  • Ulcerative colitis (UC) is characterized by a life-long chronic course with remissions and exacerbations. Use of biological therapies may reduce or delay the surgical procedures in patients with UC. The aim of this study was to determine the impact of infliximab (IFX) use on the rate of remission, surgical interventions, and the effect on quality of life in patients with moderate to severe UC. Literature was searched for studies that investigated the efficacy of IFX on the rate of remission, colectomy and quality of life (QoL) between January 1990 and June 2012 at MEDLINE, January 1988 and June 2012 at EMbase and others. Eleven trials were included in the meta-analysis; divided into placebo controlled 8 trials and intravenous corticosteroid controlled group 3 trials. In comparison to placebo control groups, patients who received IFX had an odds ratio (OR) of 3.712 (95% CI: 2.714, 5.079) for the short-term clinical remission, and 3.053 (95% CI: 2.044, 4.559) for the rate of long-term remission. In colectomy rate and quality of life (QoL), odds ratio were 0.566(95% CI: 0.387, 0.827) and 0.658 (0.505, 0.811) respectively. Any adverse reactions including infections, infusion reaction, rash and arthralgia were equivalent in both groups. Compared with intravenous corticosteroid controlled group, patients who received IFX had lower remission rate with short-term odds ratio 0.227 (95% CI: 0.033, 1.556) and long-term odds ratio 1.054 (95% CI: 0.317, 3.502) respectively. However, statistical significance was not showed with both two analyses. The higher adverse drug reaction (ADR) rates were occurred in the corticosteroid controlled groups. 73.3% of patients treated corticosteroid reported Cushing-like syndrome with moon face. In conclusion, IFX does increase remission rate and decrease the rate of colectomy in patients with UC without elevating any adverse reactions significantly. IFX also improves QoL in moderate to severe UC patients. It would not exceed the efficacy of intravenous corticosteroid, whereas intravenous corticosteroid also reported high rate of adverse reactions.

Packet Loss Fair Scheduling Scheme for Real-Time Traffic in OFDMA Systems

  • Shin, Seok-Joo;Ryu, Byung-Han
    • ETRI Journal
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    • v.26 no.5
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    • pp.391-396
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    • 2004
  • In this paper, we propose a packet scheduling discipline called packet loss fair scheduling, in which the packet loss of each user from different real-time traffic is fairly distributed according to the quality of service requirements. We consider an orthogonal frequency division multiple access (OFDMA) system. The basic frame structure of the system is for the downlink in a cellular packet network, where the time axis is divided into a finite number of slots within a frame, and the frequency axis is segmented into subchannels that consist of multiple subcarriers. In addition, to compensate for fast and slow channel variation, we employ a link adaptation technique such as adaptive modulation and coding. From the simulation results, our proposed packet scheduling scheme can support QoS differentiations while guaranteeing short-term fairness as well as long-term fairness for various real-time traffic.

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Deep reinforcement learning for base station switching scheme with federated LSTM-based traffic predictions

  • Hyebin Park;Seung Hyun Yoon
    • ETRI Journal
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    • v.46 no.3
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    • pp.379-391
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    • 2024
  • To meet increasing traffic requirements in mobile networks, small base stations (SBSs) are densely deployed, overlapping existing network architecture and increasing system capacity. However, densely deployed SBSs increase energy consumption and interference. Although these problems already exist because of densely deployed SBSs, even more SBSs are needed to meet increasing traffic demands. Hence, base station (BS) switching operations have been used to minimize energy consumption while guaranteeing quality-of-service (QoS) for users. In this study, to optimize energy efficiency, we propose the use of deep reinforcement learning (DRL) to create a BS switching operation strategy with a traffic prediction model. First, a federated long short-term memory (LSTM) model is introduced to predict user traffic demands from user trajectory information. Next, the DRL-based BS switching operation scheme determines the switching operations for the SBSs using the predicted traffic demand. Experimental results confirm that the proposed scheme outperforms existing approaches in terms of energy efficiency, signal-to-interference noise ratio, handover metrics, and prediction performance.