ICT Express最新文献_第5页

Power Allocation for Beam Alignment in Millimeter Wave IoT Communications 毫米波物联网通信中波束对准的功率分配

IF 4.1 3区计算机科学

ICT Express Pub Date : 2025-01-03 DOI: 10.1016/j.icte.2024.12.006

Jiho Song

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引用次数: 0

FedWT: Federated Learning with Minimum Spanning Tree-based Weighted Tree Aggregation for UAV networks FedWT：基于最小生成树加权树聚合的无人机网络联邦学习

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-24 DOI: 10.1016/j.icte.2024.12.005

Geonhui Kim, Jiha Kim, Yongho Kim, Hwan Kim, Hyunhee Park

{"title":"FedWT: Federated Learning with Minimum Spanning Tree-based Weighted Tree Aggregation for UAV networks","authors":"Geonhui Kim, Jiha Kim, Yongho Kim, Hwan Kim, Hyunhee Park","doi":"10.1016/j.icte.2024.12.005","DOIUrl":"10.1016/j.icte.2024.12.005","url":null,"abstract":"<div><div>In recent years, advances in communication technology, hardware, and deep learning have led to significant advancements in Unmanned Aerial Vehicles (UAVs). However, applying federated learning in UAV environments is challenging due to network instability and dependency on central server. In this paper, the Federated Learning with Minimum Spanning Tree (MST)-based Weighted Tree Aggregation (FedWT) is proposed to address transmission failure, delayed model updates, and single point of failure problems. FedWT uses MST to minimize model exchange during local aggregation, and addresses data heterogeneity through dynamic weighted averaging. It includes a decentralized federated learning method for UAVs, model sharing path scheduling to reduce communication overhead, and a flexible weight-based aggregation approach to handle data heterogeneity. Simulation results demonstrate the superior performance and communication efficiency of FedWT compared to traditional federated learning methods. In particular, FedWT achieves up to 2% higher prediction accuracy and reduces communication traffic by up to 84.98% in highly heterogeneous data scenarios. Under different network topologies, FedWT consistently outperformed other federated learning methods in terms of learning accuracy and loss reduction. Future work will optimize the dynamic weight adjustment and validate the robustness of FedWT under various scenarios.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 275-280"},"PeriodicalIF":4.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704910","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

GMT: Gzip-based Memory-efficient Time-series classification GMT：基于gzip的内存效率时间序列分类

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-13 DOI: 10.1016/j.icte.2024.12.003

Sungmin Lee , Kichang Lee , JaeYeon Park , JeongGil Ko

引用次数: 0

Optimizing proactive content caching with mobility aware deep reinforcement & asynchronous federate learning in VEC 在VEC中优化具有移动性感知的深度强化和异步联邦学习的主动内容缓存

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-02 DOI: 10.1016/j.icte.2024.11.006

Afsana Kabir Sinthia, Nosin Ibna Mahbub, Eui-Nam Huh

{"title":"Optimizing proactive content caching with mobility aware deep reinforcement & asynchronous federate learning in VEC","authors":"Afsana Kabir Sinthia, Nosin Ibna Mahbub, Eui-Nam Huh","doi":"10.1016/j.icte.2024.11.006","DOIUrl":"10.1016/j.icte.2024.11.006","url":null,"abstract":"<div><div>Edge caching in the Internet of Vehicles (IoV) can reduce backhaul strain and content access delay. However, due to the constant changes in vehicle requests, offloading applications to edge servers is crucial for efficiently anticipating and caching popular content. Additionally, conventional data-sharing techniques are inadequate for this task due to their inability to preserve the privacy of vehicular users (VU). To overcome these issues, we propose a cooperative proactive content caching system incorporating Asynchronous federated learning and Deep reinforcement learning named <strong>PCAD</strong> that leverages the strengths of Dueling Deep Q-Networks and Prioritized Experience Replay in vehicular edge computing. PCAD lowers the latency of content access by prefetching contents that are popular beforehand caching them on edge nodes and cutting the waiting time for every vehicle to complete training as well as uploading local models before updating the global model. Additionally, we investigate intelligent caching decisions based on content prediction. Comprehensive experimental evaluations indicate that our proposed approach significantly outperforms existing benchmark caching techniques. More specifically, our suggested approach works better than DDQN, c-<span><math><mi>ϵ</mi></math></span>-greedy, and PCAD without DRL methods and the cache hit rate improves by approximately 4.25%, 11.23%, and 25.82%, respectively, as the cache capacity hits 400 MB.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"11 2","pages":"Pages 293-298"},"PeriodicalIF":4.1,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704826","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

Instantaneous received signal strength-based sensor activation for energy-efficient distributed cooperative sensor networks 基于瞬时接收信号强度的传感器激活，实现高能效分布式合作传感器网络

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.05.004

Jingon Joung , Jian Zhao

引用次数: 0

Dynamic separate resource pool algorithm for vehicle-to-infrastructure communication 车辆与基础设施通信的动态分离资源池算法

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.08.002

Jicheng Yin, Shengmin Zhao, Seung-Hoon Hwang

引用次数: 0

Reduction of peak-to-average power ratio for FBMC/OQAM signals under the general linear non-symmetrical companding transform with a Laplace distribution 在拉普拉斯分布的一般线性非对称压缩变换下降低 FBMC/OQAM 信号的峰均功率比

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.05.009

Xinyu Liu , Hongkun Zhou , Xiyun Ge , Miao Yu , Lei Liu

引用次数: 0

Selfish attack detection and response using cooperative backoff adjustment in wireless sensor networks 利用无线传感器网络中的合作后退调整检测和响应自私攻击

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.05.014

Na-Eun Park, Seo-Yi Kim, Il-Gu Lee

引用次数: 0

Cooperative transmission of UAV swarm using orthogonal time–frequency space modulation 利用正交时频空间调制实现无人机群的合作传输

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.07.002

Usman Iqbal , Yejin Lee , Sunghwan Cho , In-Ho Lee , Haejoon Jung

{"title":"Cooperative transmission of UAV swarm using orthogonal time–frequency space modulation","authors":"Usman Iqbal , Yejin Lee , Sunghwan Cho , In-Ho Lee , Haejoon Jung","doi":"10.1016/j.icte.2024.07.002","DOIUrl":"10.1016/j.icte.2024.07.002","url":null,"abstract":"<div><div>Unmanned aerial vehicles (UAVs) emerge as versatile aerial nodes capable of dynamically filling coverage gaps and enabling mission-critical communication based on their mobile nature. UAV swarms, characterized by the coordinated operation of multiple drones, are employed for a wide range of applications such as surveillance, environmental monitoring, precision farming, and autonomous delivery. While individual UAVs suffer from limited power, group transmissions of UAV swarms can enhance the data rate, reliability, and energy efficiency. However, their mobility may cause severe Doppler spread. The existing orthogonal frequency division multiplexing (OFDM) system exhibits limitations such as susceptibility to the Doppler effect in high-speed mobile environments. To address this issue, orthogonal time–frequency space (OTFS)-aided cooperative transmission (CT) for UAV swarms is considered, which can surmount the aforementioned limitations. The results show the BER improvement of the order of <span><math><mrow><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>3</mn></mrow></msup></mrow></math></span> at the SNR value of 10 dB when OTFS modulation is utilized and even better at the higher SNR values. Furthermore, the analytical framework of OTFS-based CT is presented by identifying the key design considerations on the subcarrier spacing, the number of symbols, and the number of subcarriers, which are subject to the maximum speed of the UAV and the cluster size of the UAV swarm. These results provide a significant platform for advancing research in the field of UAV-based CT, especially with the Doppler-resilient OTFS modulation.</div></div>","PeriodicalId":48526,"journal":{"name":"ICT Express","volume":"10 6","pages":"Pages 1240-1246"},"PeriodicalIF":4.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141696120","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

Toward reliability-satisfied and hop-constrained backup paths for industrial internet demands 为满足工业互联网需求而开发可靠且跳数受限的备份路径

IF 4.1 3区计算机科学

ICT Express Pub Date : 2024-12-01 DOI: 10.1016/j.icte.2024.07.003

Huifen Huang , Xinchang Zhang

引用次数: 0