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RIS-aided free-space optics communications in A2G networks over inverted Gamma–Gamma turbulent channels
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
Enhancing network function parallelism in mobile edge computing using Deep Reinforcement Learning
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
A filter-and-refine approach to lightweight application traffic classification 轻量级应用流量分类的过滤与提炼方法
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.06.003
Ui-Jun Baek , Jee-Tae Park , Yoon-Seong Jang , Ju-Sung Kim , Yang-Seo Choi , Myung-Sup Kim
{"title":"A filter-and-refine approach to lightweight application traffic classification","authors":"Ui-Jun Baek ,&nbsp;Jee-Tae Park ,&nbsp;Yoon-Seong Jang ,&nbsp;Ju-Sung Kim ,&nbsp;Yang-Seo Choi ,&nbsp;Myung-Sup Kim","doi":"10.1016/j.icte.2024.06.003","DOIUrl":"10.1016/j.icte.2024.06.003","url":null,"abstract":"<div><div>As application traffic becomes increasingly complex and voluminous, the need for accurate and fast traffic classification is emphasized, leading to proposals for lightweighting DL-based classifier. Nevertheless, there is still a need for faster and more accurate classification methods for practical deployment. We propose a new traffic classification mechanism using the Filter-and-Refine approach. The proposed method was evaluated public dataset using seven baselines and showed 4%p higher accuracy and about 39 times faster classification speed compared to the state-of-the-art. The source code and dataset are available at <span><span>https://github.com/pb1069/Network-Traffic-Classification</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 1-6"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141395186","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
Multivariate bidirectional gate recurrent unit for improving accuracy of energy prediction
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
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
Fusion of self-attention mechanism for CSI feedback in massive MIMO systems
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.10.010
Tingting Zhang , Youyun Xu , Changpeng Zhou
{"title":"Fusion of self-attention mechanism for CSI feedback in massive MIMO systems","authors":"Tingting Zhang ,&nbsp;Youyun Xu ,&nbsp;Changpeng Zhou","doi":"10.1016/j.icte.2024.10.010","DOIUrl":"10.1016/j.icte.2024.10.010","url":null,"abstract":"<div><div>In massive MIMO systems, obtaining accurate channel state information (CSI) is crucial for optimal channel coding and beamforming. However, traditional CSI feedback methods require high bandwidth and also consume a large amount of power and computing resources. To address these challenges, several compressed sensing-based techniques have been implemented in recent years. These techniques, however, are often iterative and computationally complex to implement in power-constrained user equipment. In this paper, we propose a novel fusion of the self-attention mechanism, called <em>FSAMNet</em>, to efficiently and accurately implement the CSI feedback task for massive MIMO systems. Our proposed FSAMNet adopts both the residual connections in the attention mechanism and a sequence of depth-separable convolutional layers to enhance the model’s performance and expressive ability. Specifically, we apply a multi-layer self-attention mechanism in the encoder part to achieve feature extraction and compression. In the decoder part, we use multiple convolutional layers and self-attention mechanisms to convert the embedding vector generated by the encoder back into the original image. Experimental results show that the performance of our proposed FSAMNet outperforms conventional benchmark schemes in terms of feedback network performance.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 124-128"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421281","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 transparency and trust in AI-powered manufacturing: A survey of explainable AI (XAI) applications in smart manufacturing in the era of industry 4.0/5.0
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.12.001
Konstantinos Nikiforidis , Alkiviadis Kyrtsoglou , Thanasis Vafeiadis , Thanasis Kotsiopoulos , Alexandros Nizamis , Dimosthenis Ioannidis , Konstantinos Votis , Dimitrios Tzovaras , Panagiotis Sarigiannidis
{"title":"Enhancing transparency and trust in AI-powered manufacturing: A survey of explainable AI (XAI) applications in smart manufacturing in the era of industry 4.0/5.0","authors":"Konstantinos Nikiforidis ,&nbsp;Alkiviadis Kyrtsoglou ,&nbsp;Thanasis Vafeiadis ,&nbsp;Thanasis Kotsiopoulos ,&nbsp;Alexandros Nizamis ,&nbsp;Dimosthenis Ioannidis ,&nbsp;Konstantinos Votis ,&nbsp;Dimitrios Tzovaras ,&nbsp;Panagiotis Sarigiannidis","doi":"10.1016/j.icte.2024.12.001","DOIUrl":"10.1016/j.icte.2024.12.001","url":null,"abstract":"<div><div>Explainable Artificial Intelligence (XAI) is crucial for the transition from the fourth to fifth industrial revolution, providing transparency and fostering user confidence in Artificial Intelligence (AI) powered systems. Since 2020, XAI applications demonstrate potential to transform manufacturing. This paper provides an extensive overview of XAI-based applications in Industries 4.0 and 5.0 by highlighting the trends regarding methods used, connecting XAI methods with important parameters and presenting XAI visualization approaches. The survey provides valuable insights for researchers, practitioners and industry leaders as it underscores the potential of XAI in shaping the future of manufacturing by enhancing transparency and user acceptance of AI-powered applications.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 135-148"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421283","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
Handover strategy for LEO satellite communication using graph neural network
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2025.01.009
Ji-Woon Lee , Byungju Lim , Ki-Hun Kim , Jong-Man Lee , Young-Seok Ha , Young-Jin Han , Young-Chai Ko
{"title":"Handover strategy for LEO satellite communication using graph neural network","authors":"Ji-Woon Lee ,&nbsp;Byungju Lim ,&nbsp;Ki-Hun Kim ,&nbsp;Jong-Man Lee ,&nbsp;Young-Seok Ha ,&nbsp;Young-Jin Han ,&nbsp;Young-Chai Ko","doi":"10.1016/j.icte.2025.01.009","DOIUrl":"10.1016/j.icte.2025.01.009","url":null,"abstract":"<div><div>Distributed handover (HO) strategy with low complexity can provide seamless communication in low earth orbit (LEO) satellite networks. However, it is difficult to consider load balancing in distributed HO strategy, which may results in HO failures. In this paper, we propose a graph neural network (GNN) based distributed HO strategy for LEO satellite communication to maximize sum rate by considering load balancing. We first propose target satellite selection method with GNN where each user equipment (UE) selects target satellite and requests HO to it. We then employ ACK decision policy to strictly satisfy load balancing of satellites where each satellite decides HO requests from UEs depending on its load condition. To validate the proposed GNN based HO, we use the System Tool Kit (STK) for modeling LEO satellites with 22 orbits and 72 satellites are in each orbit, and evaluate the HO process during 2400 s. From this constellation, we generate 9,600 samples by randomly deploying UEs on the ground and use them as dataset. Simulation results show that the proposed GNN based HO strategy outperforms conventional HO strategies by selecting an appropriate target satellite. We also demonstrate that load balancing is satisfied due to ACK decision policy and the scalability of proposed GNN architecture is ensured with different network sizes.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 239-244"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704776","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
Optimizing Crystals-Dilithium implementation in 16-bit MSP430 environment utilizing hardware multiplier
IF 4.1 3区 计算机科学
ICT Express Pub Date : 2025-02-01 DOI: 10.1016/j.icte.2024.09.019
DongHyun Shin, YoungBeom Kim, Seog Chung Seo
{"title":"Optimizing Crystals-Dilithium implementation in 16-bit MSP430 environment utilizing hardware multiplier","authors":"DongHyun Shin,&nbsp;YoungBeom Kim,&nbsp;Seog Chung Seo","doi":"10.1016/j.icte.2024.09.019","DOIUrl":"10.1016/j.icte.2024.09.019","url":null,"abstract":"<div><div>Dilithium was selected as one of NIST standard Post Quantum Digital Signature algorithms and is undergoing standardization as a Module Lattice Digital Signature Algorithm (ML-DSA). However, until now research on optimization in embedded environments has primarily been conducted on ARM architectures, which are the basic benchmark targets. To prepare for future quantum secure Internet of Things environments, performance optimization on resource-constrained must be considered. Thus, in this paper, for the first time, we propose an optimized implementation of Dilithium in the 16-bit MSP430 environment, a low-resource device. We redesign the state-of-the-art optimization strategies for Dilithium to suit the MSP430 environment. By taking full advantage of MSP430’s hardware multiplier in the NTT-based polynomial multiplication, we achieve 73.0% and 80.1% of performance improvement for NTT and NTT<sup>−1</sup> compared to those in the reference implementation, which contributes about 5.5%–7.0%, 15.3%–17.5%, and 7.5%–10.0% of performance improvement compared to Dilithium’s public reference implementation for keypair generation, signing, and verification, respectively.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 1","pages":"Pages 59-65"},"PeriodicalIF":4.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421204","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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