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Evidential reasoning rule with dynamic reliability for performance assessment of wireless sensor network 基于动态可靠度的无线传感器网络性能评估证据推理规则
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.08.009
Yue Han , Rui-Feng Yu , Jie Wang , Shuai Yan , Shi-Wei Huo , Fu-Quan Li
{"title":"Evidential reasoning rule with dynamic reliability for performance assessment of wireless sensor network","authors":"Yue Han ,&nbsp;Rui-Feng Yu ,&nbsp;Jie Wang ,&nbsp;Shuai Yan ,&nbsp;Shi-Wei Huo ,&nbsp;Fu-Quan Li","doi":"10.1016/j.icte.2024.08.009","DOIUrl":"10.1016/j.icte.2024.08.009","url":null,"abstract":"<div><div>The performance of wireless sensor network (WSN) continues to change over time, and it is required to track the WSN performance accurately. In this paper, a new assessment model known as the evidential reasoning rule with dynamic reliability (ERr-DR) is proposed. In the ERr-DR, the evidence reliability evolves from the traditional static value to a dynamic value, which can reveal the impact of external noise on network performance reasonably. As an effective extension of traditional ER rule, the ERr-DR has excellent modeling ability. Furthermore, by analyzing the physical meanings of model parameters in detail, an optimization objective with targeted constraints is established. Compared with the existing optimization strategies, this not only improves the output accuracy of ERr-DR, but also maintains the interpretability of assessment results. Finally, A case study of a simulated WSN scenario validates the effectiveness of the proposed model.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 19-25"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Transactional dynamics in hyperledger fabric: A stochastic modeling and performance evaluation of permissioned blockchains 超级账本结构中的交易动态：许可区块链的随机建模和性能评估
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.10.009
Carlos Melo , Glauber Gonçalves , Francisco Airton Silva , Iure Fé , Ericksulino Moura , André Soares , Eunmi Choi , Dugki Min , Jae-Woo Lee , Tuan Anh Nguyen
{"title":"Transactional dynamics in hyperledger fabric: A stochastic modeling and performance evaluation of permissioned blockchains","authors":"Carlos Melo ,&nbsp;Glauber Gonçalves ,&nbsp;Francisco Airton Silva ,&nbsp;Iure Fé ,&nbsp;Ericksulino Moura ,&nbsp;André Soares ,&nbsp;Eunmi Choi ,&nbsp;Dugki Min ,&nbsp;Jae-Woo Lee ,&nbsp;Tuan Anh Nguyen","doi":"10.1016/j.icte.2024.10.009","DOIUrl":"10.1016/j.icte.2024.10.009","url":null,"abstract":"<div><div>Blockchain, often integrated with distributed systems and security enhancements, has significant potential in various industries. However, environmental concerns and the efficiency of consortia-controlled permissioned networks remain critical issues. We use a Stochastic Petri Net model to analyze transaction flows in Hyperledger Fabric networks, achieving a 95% confidence interval for response times. This model enables administrators to assess the impact of system changes on resource utilization. Sensitivity analysis reveals major factors influencing response times and throughput. Our case studies demonstrate that block size can alter throughput and response times by up to 200%, underscoring the need for performance optimization with resource efficiency.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 87-92"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cross-domain autonomous driving visual segmentation based on enhanced target data learning 基于增强目标数据学习的跨域自动驾驶视觉分割
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.020
Chaoyu Rao , Xiaoyong Fang , Yunzhe Zhang , Wanshu Fan , Dongsheng Zhou
{"title":"Cross-domain autonomous driving visual segmentation based on enhanced target data learning","authors":"Chaoyu Rao ,&nbsp;Xiaoyong Fang ,&nbsp;Yunzhe Zhang ,&nbsp;Wanshu Fan ,&nbsp;Dongsheng Zhou","doi":"10.1016/j.icte.2024.09.020","DOIUrl":"10.1016/j.icte.2024.09.020","url":null,"abstract":"<div><div>Within the broader context of Information and Communications Technology (ICT), the quest for reliable and scalable visual segmentation methods poses significant challenges, particularly in autonomous driving, where real-world scene complexity requires advanced solutions. To address data scarcity and improve segmentation performance, we propose a novel unsupervised domain adaptation (UDA) approach that enhances target domain learning. Our method introduces multiple perturbations consistency, leveraging spatial context within the target domain to improve recognition. By applying perturbations at input and feature levels and using a consistency loss, we enhance contextual learning. Additionally, a weight mapping technique reduces the impact of detrimental source domain information. Experimental results demonstrate that our approach outperforms baseline methods on the GTAV<span><math><mo>→</mo></math></span>Cityscapes and SYNTHIA<span><math><mo>→</mo></math></span>Cityscapes datasets.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 53-58"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
RIS reflection pattern design for vehicular platoon communications in mmWave channels 毫米波信道下车辆排通信的RIS反射模式设计
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.10.004
Jong-Ho Lee, Jiho Song
{"title":"RIS reflection pattern design for vehicular platoon communications in mmWave channels","authors":"Jong-Ho Lee,&nbsp;Jiho Song","doi":"10.1016/j.icte.2024.10.004","DOIUrl":"10.1016/j.icte.2024.10.004","url":null,"abstract":"<div><div>In this paper, we propose a reflection pattern design scheme for reconfigurable intelligent surface (RIS) assisted vehicular platoon communications in millimeter wave (mmWave) channels. We focus on optimizing the reflection pattern of a RIS that is installed in a roadside unit to maximize the broadcast information rate from the lead vehicle in a platoon to each following member vehicle. We show that this problem can be effectively solved using semidefinite programming. Next, we propose a reflection pattern design scheme for the RIS that maximizes its reflection gain by exploiting the angle of departure, angle of arrival, and path loss information between each vehicle and the RIS in mmWave channels. Finally, we present numerical results that demonstrate the effectiveness of our proposed reflection pattern design scheme.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 105-109"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Addressing data scarcity in speech emotion recognition: A comprehensive review 解决语音情感识别中的数据稀缺性：一个全面的综述
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.11.003
Samuel Kakuba , Dong Seog Han
{"title":"Addressing data scarcity in speech emotion recognition: A comprehensive review","authors":"Samuel Kakuba ,&nbsp;Dong Seog Han","doi":"10.1016/j.icte.2024.11.003","DOIUrl":"10.1016/j.icte.2024.11.003","url":null,"abstract":"<div><div>Speech emotion recognition (SER) is a critical field within affective computing, aiming to detect and classify emotional states from speech signals, which vary dynamically over time. These signals encode complex relationships between features at multiple time scales, effectively reflecting a speaker’s emotional state. Despite significant progress, SER faces the persistent challenge of labeled data scarcity, a major obstacle given the data-intensive requirements of deep learning models. This scarcity often results in small, imbalanced datasets that hinder model generalization. Various strategies, including feature selection, data augmentation, domain adaptation, and fusion techniques, have been employed to mitigate these issues. However, comprehensive reviews that critically analyze these methods remain limited. In this paper, we provide an extensive review of these data scarcity strategies in SER, assessing their merits and limitations in terms of efficiency and robustness. Special attention is given to how these strategies enhance the performance of both acoustic and multimodal SER systems when operating on limited datasets. Additionally, we highlight the potential of fusion strategies combined with attention mechanisms as promising solutions to improve convergence and reduce model complexity.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 110-123"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing network function parallelism in mobile edge computing using Deep Reinforcement Learning 利用深度强化学习增强移动边缘计算中的网络功能并行性
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.011
DongYu Lu , Shirong Long
{"title":"Enhancing network function parallelism in mobile edge computing using Deep Reinforcement Learning","authors":"DongYu Lu ,&nbsp;Shirong Long","doi":"10.1016/j.icte.2024.09.011","DOIUrl":"10.1016/j.icte.2024.09.011","url":null,"abstract":"<div><div>This paper introduces a Deep Reinforcement Learning (DRL)-based framework to enhance Network Function Parallelism (NFP) in Mobile Edge Computing (MEC). Leveraging Network Function Virtualization (NFV), the proposed framework optimizes service delay by solving a fairness-aware throughput maximization problem for service function chain placement. It aims to maximize the long-term cumulative reward while satisfying Quality of Service (QoS) requirements. The framework also preserves resources for future requests by efficiently managing the initialized network functions distribution. Simulation results demonstrate the superior performance of the proposed framework across various metrics. Specifically, our framework improves the average delay and deployment rate by 1.2% and 2.4% compared to the existing best method.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 41-46"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
RIS-aided free-space optics communications in A2G networks over inverted Gamma–Gamma turbulent channels 反向伽玛-伽玛湍流信道上的A2G网络中的ris辅助自由空间光学通信
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.016
Md. Abdur Rakib , Md. Ibrahim , A.S.M. Badrudduza , Imran Shafique Ansari , Md. Shahid Uz Zaman , Heejung Yu
{"title":"RIS-aided free-space optics communications in A2G networks over inverted Gamma–Gamma turbulent channels","authors":"Md. Abdur Rakib ,&nbsp;Md. Ibrahim ,&nbsp;A.S.M. Badrudduza ,&nbsp;Imran Shafique Ansari ,&nbsp;Md. Shahid Uz Zaman ,&nbsp;Heejung Yu","doi":"10.1016/j.icte.2024.09.016","DOIUrl":"10.1016/j.icte.2024.09.016","url":null,"abstract":"<div><div>Reconfigurable intelligent surfaces (RISs) have revolutionized free-space optics (FSO) communication by dynamically optimizing the propagation environment. This study proposes a framework to analyze RIS-assisted FSO communication over inverted Gamma–Gamma (IGGG) distributions. We use the IGGG distribution for air-to-ground networks, accurately modeling atmospheric turbulence. Consequently, we derived performance metrics in terms of Meijer’s G by employing an asymptotic analysis to provide deeper insights. Our results demonstrate incorporating RISs into our proposed network enhances outage performance by 52.08% at a SNR of 30 dB. Furthermore, the results highlight the importance of heterodyne detection in mitigating the adverse effects of pointing errors.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 66-73"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multivariate bidirectional gate recurrent unit for improving accuracy of energy prediction 用于提高能量预测精度的多元双向栅极循环单元
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.10.002
Quota Alief Sias, Rahma Gantassi, Yonghoon Choi
{"title":"Multivariate bidirectional gate recurrent unit for improving accuracy of energy prediction","authors":"Quota Alief Sias,&nbsp;Rahma Gantassi,&nbsp;Yonghoon Choi","doi":"10.1016/j.icte.2024.10.002","DOIUrl":"10.1016/j.icte.2024.10.002","url":null,"abstract":"<div><div>Energy prediction is an important process in energy management, especially regarding demand response. Energy predictions are often carried out for load forecasting or energy generation forecasting of renewable energy. This paper explains the implementation of multi-variables in the development of recurrence neural network models to predict load energy and generation energy. The proposed main model is a multi-variate bidirectional GRU combined with a periodic feature pattern. The proposed model will also be compared with the fundamental bidirectional models of the GRU and LSTM models. For load prediction, the variables used are all energy supply data and periodic features. Meanwhile, for photovoltaic generation energy predictions, additional weather data is used because energy generation is very dependent on solar radiation and ambient conditions. Load prediction data is built using daily and hourly energy prediction data. Meanwhile, solar energy prediction is constructed with data every minute. The results show that the proposed model obtains the best prediction results for all test data on a daily, hourly, or minute basis. The model also shows the fastest execution time performance compared to other models.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 80-86"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fast and fair split computing for accelerating deep neural network (DNN) inference 快速和公平的分割计算加速深度神经网络（DNN）推理
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.013
Dongju Cha , Jaewook Lee , Daeyoung Jung, Sangheon Pack
{"title":"Fast and fair split computing for accelerating deep neural network (DNN) inference","authors":"Dongju Cha ,&nbsp;Jaewook Lee ,&nbsp;Daeyoung Jung,&nbsp;Sangheon Pack","doi":"10.1016/j.icte.2024.09.013","DOIUrl":"10.1016/j.icte.2024.09.013","url":null,"abstract":"<div><div>Conventional split computing approaches for AI models that generate large outputs suffer from long transmission and inference times. Due to the limited resources of the edge server and selfish MDs, some MDs cannot offload their tasks and sacrifice their performance. To address these issues, we formulate an optimization problem to determine one or two split points that minimize inference latency while ensuring fair offloading among MDs. Additionally, we devise a low-complexity heuristic algorithm called fast and fair split computing (F2SC). Evaluation results demonstrate that F2SC reduces inference time by <span><math><mrow><mn>3</mn><mo>.</mo><mn>8</mn><mtext>%</mtext><mo>∼</mo><mn>20</mn><mo>.</mo><mn>1</mn><mtext>%</mtext></mrow></math></span> compared to the conventional approaches while maintaining fairness.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 47-52"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning to route and schedule links in reconfigurable networks 在可重构网络中学习路由和调度链路
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.07.001
Xiangdong Yi, Kwan-Wu Chin
{"title":"Learning to route and schedule links in reconfigurable networks","authors":"Xiangdong Yi,&nbsp;Kwan-Wu Chin","doi":"10.1016/j.icte.2024.07.001","DOIUrl":"10.1016/j.icte.2024.07.001","url":null,"abstract":"<div><div>This paper considers networks with a reconfigurable topology with so called 60 GHz dynamic links that can be activated or disabled over time. A fundamental problem is to jointly determine which 60 GHz dynamic links are active and the route chosen by source nodes over time. To this end, this paper outlines a hierarchical deep reinforcement learning solution that can be used to compute the optimal policy that determines for each time slot (i) active dynamic links, and (ii) the route used by each source–destination pair. The results show that the proposed approach results in a maximum average queue length that is 80% shorter than non-learning methods.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 7-12"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141707794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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