Digital Communications and Networks最新文献

Demand side management with wireless channel impact in IoT-enabled smart grid system 基于物联网的智能电网系统中无线信道影响的需求侧管理

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.06.005

Md. Farhad Hossain , Kumudu S. Munasinghe , Nishant Jagannath , Khandakar Tanvir Ahmed , Md. Nabid Hasan , Ibrahim Elgendi , Abbas Jamalipour

{"title":"Demand side management with wireless channel impact in IoT-enabled smart grid system","authors":"Md. Farhad Hossain , Kumudu S. Munasinghe , Nishant Jagannath , Khandakar Tanvir Ahmed , Md. Nabid Hasan , Ibrahim Elgendi , Abbas Jamalipour","doi":"10.1016/j.dcan.2024.06.005","DOIUrl":"10.1016/j.dcan.2024.06.005","url":null,"abstract":"<div><div>Demand Side Management (DSM) is a vital issue in smart grids, given the time-varying user demand for electricity and power generation cost over a day. On the other hand, wireless communications with ubiquitous connectivity and low latency have emerged as a suitable option for smart grid. The design of any DSM system using a wireless network must consider the wireless link impairments, which is missing in existing literature. In this paper, we propose a DSM system using a Real-Time Pricing (RTP) mechanism and a wireless Neighborhood Area Network (NAN) with data transfer uncertainty. A Zigbee-based Internet of Things (IoT) model is considered for the communication infrastructure of the NAN. A sample NAN employing XBee and Raspberry Pi modules is also implemented in real-world settings to evaluate its reliability in transferring smart grid data over a wireless link. The proposed DSM system determines the optimal price corresponding to the optimum system welfare based on the two-way wireless communications among users, decision-makers, and energy providers. A novel cost function is adopted to reduce the impact of changes in user numbers on electricity prices. Simulation results indicate that the proposed system benefits users and energy providers. Furthermore, experimental results demonstrate that the success rate of data transfer significantly varies over the implemented wireless NAN, which can substantially impact the performance of the proposed DSM system. Further simulations are then carried out to quantify and analyze the impact of wireless communications on the electricity price, user welfare, and provider welfare.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 493-504"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TRE-DSP: A traceable and revocable CP-ABE based data sharing scheme for IoV with partially hidden policy TRE-DSP：基于CP-ABE的可追溯和可撤销的物联网数据共享方案，具有部分隐藏策略

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.03.005

Yousheng Zhou , Rundong Peng , Yuanni Liu , Pandi Vijayakumar , Brij Gupta

{"title":"TRE-DSP: A traceable and revocable CP-ABE based data sharing scheme for IoV with partially hidden policy","authors":"Yousheng Zhou , Rundong Peng , Yuanni Liu , Pandi Vijayakumar , Brij Gupta","doi":"10.1016/j.dcan.2024.03.005","DOIUrl":"10.1016/j.dcan.2024.03.005","url":null,"abstract":"<div><div>With the popularity of the Internet of Vehicles (IoV), a large amount of data is being generated every day. How to securely share data between the IoV operator and various value-added service providers becomes one of the critical issues. Due to its flexible and efficient fine-grained access control feature, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is suitable for data sharing in IoV. However, there are many flaws in most existing CP-ABE schemes, such as attribute privacy leakage and key misuse. This paper proposes a Traceable and Revocable CP-ABE-based Data Sharing with Partially hidden policy for IoV (TRE-DSP). A partially hidden access structure is adopted to hide sensitive user attribute values, and attribute categories are sent along with the ciphertext to effectively avoid privacy exposure. In addition, key tracking and malicious user revocation are introduced with broadcast encryption to prevent key misuse. Since the main computation task is outsourced to the cloud, the burden of the user side is relatively low. Analysis of security and performance demonstrates that TRE-DSP is more secure and practical for data sharing in IoV.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 455-464"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140279006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Handover management in beyond 5G HetNet topologies with unbalanced user distribution 用户分布不均衡的超 5G Hetnet 拓扑中的切换管理

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.05.005

Abdussamet Hatipoglu , Mehmet Akif Yazici , Mehmet Basaran , Mine Ardanuc , Lutfiye Durak-Ata

引用次数: 0

Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network 基于高光谱成像和一维卷积神经网络的含杂质籽棉的无损检测与分类

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.05.008

Yeqi Fei , Zhenye Li , Tingting Zhu , Zengtao Chen , Chao Ni

{"title":"Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network","authors":"Yeqi Fei , Zhenye Li , Tingting Zhu , Zengtao Chen , Chao Ni","doi":"10.1016/j.dcan.2024.05.008","DOIUrl":"10.1016/j.dcan.2024.05.008","url":null,"abstract":"<div><div>The cleanliness of seed cotton plays a critical role in the pre-treatment of cotton textiles, and the removal of impurity during the harvesting process directly determines the quality and market value of cotton textiles. By fusing band combination optimization with deep learning, this study aims to achieve more efficient and accurate detection of film impurities in seed cotton on the production line. By applying hyperspectral imaging and a one-dimensional deep learning algorithm, we detect and classify impurities in seed cotton after harvest. The main categories detected include pure cotton, conveyor belt, film covering seed cotton, and film adhered to the conveyor belt. The proposed method achieves an impurity detection rate of 99.698%. To further ensure the feasibility and practical application potential of this strategy, we compare our results against existing mainstream methods. In addition, the model shows excellent recognition performance on pseudo-color images of real samples. With a processing time of 11.764 μs per pixel from experimental data, it shows a much improved speed requirement while maintaining the accuracy of real production lines. This strategy provides an accurate and efficient method for removing impurities during cotton processing.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 308-316"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141277732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RS-DRL-based offloading policy and UAV trajectory design in F-MEC systems 基于 RS-DRL 的 F-MEC 系统卸载策略和无人机轨迹设计

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2023.12.005

Yulu Yang , Han Xu , Zhu Jin , Tiecheng Song , Jing Hu , Xiaoqin Song

引用次数: 0

High-speed encrypted traffic classification by using payload features 利用有效载荷特征进行高速加密流量分类

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.02.003

Xinge Yan , Liukun He , Yifan Xu , Jiuxin Cao , Liangmin Wang , Guyang Xie

{"title":"High-speed encrypted traffic classification by using payload features","authors":"Xinge Yan , Liukun He , Yifan Xu , Jiuxin Cao , Liangmin Wang , Guyang Xie","doi":"10.1016/j.dcan.2024.02.003","DOIUrl":"10.1016/j.dcan.2024.02.003","url":null,"abstract":"<div><div>Traffic encryption techniques facilitate cyberattackers to hide their presence and activities. Traffic classification is an important method to prevent network threats. However, due to the tremendous traffic volume and limitations of computing, most existing traffic classification techniques are inapplicable to the high-speed network environment. In this paper, we propose a High-speed Encrypted Traffic Classification (HETC) method containing two stages. First, to efficiently detect whether traffic is encrypted, HETC focuses on randomly sampled short flows and extracts aggregation entropies with chi-square test features to measure the different patterns of the byte composition and distribution between encrypted and unencrypted flows. Second, HETC introduces binary features upon the previous features and performs fine-grained traffic classification by combining these payload features with a Random Forest model. The experimental results show that HETC can achieve a 94% F-measure in detecting encrypted flows and a 85%–93% F-measure in classifying fine-grained flows for a 1-KB flow-length dataset, outperforming the state-of-the-art comparison methods. Meanwhile, HETC does not need to wait for the end of the flow and can extract mass computing features. The average time for HETC to process each flow is only 2 or 16 ms, which is lower than the flow duration in most cases, making it a good candidate for high-speed traffic classification.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 412-423"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140469139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adjustable random linear network coding (ARLNC): A solution for data transmission in dynamic IoT computational environments 可调随机线性网络编码（ARLNC）：动态物联网计算环境中的数据传输解决方案

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.04.003

Raffi Dilanchian, Ali Bohlooli, Kamal Jamshidi

{"title":"Adjustable random linear network coding (ARLNC): A solution for data transmission in dynamic IoT computational environments","authors":"Raffi Dilanchian, Ali Bohlooli, Kamal Jamshidi","doi":"10.1016/j.dcan.2024.04.003","DOIUrl":"10.1016/j.dcan.2024.04.003","url":null,"abstract":"<div><div>In mobile computing environments, most IoT devices connected to networks experience variable error rates and possess limited bandwidth. The conventional method of retransmitting lost information during transmission, commonly used in data transmission protocols, increases transmission delay and consumes excessive bandwidth. To overcome this issue, forward error correction techniques, e.g., Random Linear Network Coding (RLNC) can be used in data transmission. The primary challenge in RLNC-based methodologies is sustaining a consistent coding ratio during data transmission, leading to notable bandwidth usage and transmission delay in dynamic network conditions. Therefore, this study proposes a new block-based RLNC strategy known as Adjustable RLNC (ARLNC), which dynamically adjusts the coding ratio and transmission window during runtime based on the estimated network error rate calculated via receiver feedback. The calculations in this approach are performed using a Galois field with the order of 256. Furthermore, we assessed ARLNC's performance by subjecting it to various error models such as Gilbert Elliott, exponential, and constant rates and compared it with the standard RLNC. The results show that dynamically adjusting the coding ratio and transmission window size based on network conditions significantly enhances network throughput and reduces total transmission delay in most scenarios. In contrast to the conventional RLNC method employing a fixed coding ratio, the presented approach has demonstrated significant enhancements, resulting in a 73% decrease in transmission delay and a 4 times augmentation in throughput. However, in dynamic computational environments, ARLNC generally incurs higher computational costs than the standard RLNC but excels in high-performance networks.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 574-586"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141030523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

YOLO-SDLUWD: YOLOv7-based small target detection network for infrared images in complex backgrounds YOLO-SDLUWD：基于 YOLOv7 的复杂背景下红外图像小目标检测网络

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2023.11.001

Jinxiu Zhu , Chao Qin , Dongmin Choi

{"title":"YOLO-SDLUWD: YOLOv7-based small target detection network for infrared images in complex backgrounds","authors":"Jinxiu Zhu , Chao Qin , Dongmin Choi","doi":"10.1016/j.dcan.2023.11.001","DOIUrl":"10.1016/j.dcan.2023.11.001","url":null,"abstract":"<div><div>Infrared small-target detection has important applications in many fields due to its high penetration capability and detection distance. This study introduces a detector called “YOLO-SDLUWD” which is based on the YOLOv7 network, for small target detection in complex infrared backgrounds. The “SDLUWD” refers to the combination of the Spatial Depth layer followed Convolutional layer structure (SD-Conv) and a Linear Up-sampling fusion Path Aggregation Feature Pyramid Network (LU-PAFPN) and a training strategy based on the normalized Gaussian Wasserstein Distance loss (WD-loss) function. “YOLO-SDLUWD” aims to reduce detection accuracy when the maximum pooling downsampling layer in the backbone network loses important feature information, support the interaction and fusion of high-dimensional and low-dimensional feature information, and overcome the false alarm predictions induced by noise in small target images. The detector achieved a [email protected] of 90.4% and [email protected]:0.95 of 48.5% on IRIS-AG, an increase of 9%-11% over YOLOv7-tiny, outperforming other state-of-the-art target detectors in terms of accuracy and speed.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 269-279"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138623224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Blockchain-based knowledge-aware semantic communications for remote driving image transmission 基于区块链的远程驾驶图像传输知识感知语义通信

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2024.08.007

Yangfei Lin , Tutomu Murase , Yusheng Ji , Wugedele Bao , Lei Zhong , Jie Li

{"title":"Blockchain-based knowledge-aware semantic communications for remote driving image transmission","authors":"Yangfei Lin , Tutomu Murase , Yusheng Ji , Wugedele Bao , Lei Zhong , Jie Li","doi":"10.1016/j.dcan.2024.08.007","DOIUrl":"10.1016/j.dcan.2024.08.007","url":null,"abstract":"<div><div>Remote driving, an emergent technology enabling remote operations of vehicles, presents a significant challenge in transmitting large volumes of image data to a central server. This requirement outpaces the capacity of traditional communication methods. To tackle this, we propose a novel framework using semantic communications, through a region of interest semantic segmentation method, to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data. To solve the knowledge base inconsistencies inherent in semantic communications, we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases. This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management. Additionally, the implementation of blockchain sharding handles differentiated knowledge bases for various tasks, thus boosting overall blockchain efficiency. Experimental results show a great reduction in latency by sharding and an increase in model accuracy, confirming our framework's effectiveness.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"11 2","pages":"Pages 317-325"},"PeriodicalIF":7.5,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sparse graph neural network aided efficient decoder for polar codes under bursty interference 突发干扰下稀疏图神经网络辅助极化码高效解码器

IF 7.5 2区计算机科学

Digital Communications and Networks Pub Date : 2025-04-01 DOI: 10.1016/j.dcan.2023.12.002

Shengyu Zhang , Zhongxiu Feng , Zhe Peng , Lixia Xiao , Tao Jiang

引用次数: 0