{"title":"A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media","authors":"Yuhe Gao, Jishen Jia, Lei Cai, Meng Zhou, Haojie Chai, Jinze Jia","doi":"10.1155/2024/8442383","DOIUrl":"https://doi.org/10.1155/2024/8442383","url":null,"abstract":"Uneven water-air media distribution or irregular liquid flow can cause changes in light propagation, leading to blurring and distortion of the extracted image, which presents a challenge for object recognition accuracy. To address these issues, this paper proposes a repair network to correct object image distortion in water-air cross-media. Firstly, convolutional combination performs feature extraction on water-air cross-media images, which retains the same features at the same scale and marks feature points with large differences. Then, an attention correction module for geometric lines is proposed to correct geometric lines in water-air cross-media images by comparing and sensing the marked feature points with large differences and utilizing the line similarity in positive and negative samples. Finally, the blurring artifact elimination module eliminates artifacts caused by image blurring and geometric line correction by using multiscale fusion of individual U-Net information streams. This completes the image restoration of object distortion under water-air cross-media. The proposed method is feasible and effective for restoring aberrated objects in water-air cross-media environments, with numerous experiments conducted on water-air cross-media image datasets.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140672779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intrusion Detection Model for Wireless Sensor Networks Based on FedAvg and XGBoost Algorithm","authors":"Hongjiao Wu","doi":"10.1155/2024/5536615","DOIUrl":"https://doi.org/10.1155/2024/5536615","url":null,"abstract":"For the characteristics of channel instability in wireless sensor networks, this paper proposes an intrusion detection algorithm based on FedAvg (federated averaging) and XGBoost (extreme gradient boosting) wireless sensor networks using fog computing architecture. First, the network edge is extended by introducing fog computing nodes to reduce the communication delay. It reduces the transmission bandwidth and privacy leakage risk while improving the accuracy of jointly learned global and local models. Then, the histogram-based approximation calculation method is improved to adapt to the unbalanced data characteristics of wireless sensor networks. Finally, by introducing TOP-K gradient selection, the number of model parameter uploads is minimized, and the efficiency of model parameter interaction is improved. The experimental results show that this algorithm has superior detection performance and low energy consumption. It is also compared with other algorithms to demonstrate the high detection rate and low computational complexity of this algorithm.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140382830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques","authors":"Hye-Sook Jang, Jae-Hyoung An, Hee-Chang Eun","doi":"10.1155/2024/6684449","DOIUrl":"https://doi.org/10.1155/2024/6684449","url":null,"abstract":"This study presents frequency-based substructuring (FBS) techniques and an identification method for predicting joint parameters. Two FBS techniques, FBS-1 and FBS-2, were derived by assuming pseudomasses at the joint nodes between adjacent substructures. It is estimated that the main reason for the discrepancy with the analytical FRFs is the difficulty in describing the low-frequency responses owing to the assumed pseudomasses of the substructures. Although the FRF curve based on the FBS-2 technique is very close to the analytical FRF curve up to the first resonance frequency, some inconsistencies occur thereafter. It is analyzed that the FRFs up to the first resonance frequency can be utilized for data expansion methods and system identification techniques. Paying attention to this result, this study also provides an identification method to estimate the joint parameters based on the FRF variation. Its validity is illustrated using a numerical example.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140429127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization Algorithm for AoI-Based UAV-Assisted Data Collection","authors":"Xiaoya Zhou, Qi Zhu","doi":"10.1155/2024/6691579","DOIUrl":"https://doi.org/10.1155/2024/6691579","url":null,"abstract":"Regarding the issue of information freshness in systems that aid in data collection using unmanned aerial vehicles (UAVs), a data collection algorithm that is based on freshness and UAV assistance is proposed. Under the limitations of wireless sensor node communication distance and UAV parameters, the optimization problem of minimizing the average spatial correlation age of information (SCAoI) of all nodes in the area is set up. This problem is solved by optimizing the number of clusters, UAV flight trajectories, and the order of data collection from cluster member nodes. The maximum communication distance of the nodes is used as the cluster formation radius, and the maximum-minimum distance clustering algorithm is used to cluster the nodes in the region to obtain the minimum number of clusters. After it has been proven that the trajectory optimization problem in this study is NP-hard, the ant colony algorithm is applied to obtain the minimum flight time and the corresponding trajectory. By using the greedy algorithm to determine the member nodes in the sequence of data collection for a cluster, the instantaneous SCAoI of the UAV arriving at the cluster head is solved. Simulation results show that the proposed algorithm in this paper can effectively improve the freshness of data and reduce the average SCAoI of the system compared with the algorithm in the comparative literature, reducing the average SCAoI by about 61%.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140451290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Hybrid Heuristic Model for Duty Cycle Framework Optimization","authors":"K. Ansah, J. K. Appati, E. Owusu, J. Abdulai","doi":"10.1155/2024/9972429","DOIUrl":"https://doi.org/10.1155/2024/9972429","url":null,"abstract":"This paper proposes a hybrid metaheuristic approach to optimize a duty cycle framework based on Seagull and Mayfly Optimization (HSMO-DC) Algorithm. This approach becomes crucial as current clustering protocols are unable to efficiently tune the clustering parameters in accordance to the diversification of varying WSNs. The proposed HSMO-DC primarily has two parts, where the first part takes care of the online cluster head selection and network communication using the seagull algorithm while the second part performs parameter optimization using the mayfly algorithm. The seagull is aimed at improving the energy distribution in the network through an effective bandwidth allocation procedure while reducing the total energy dissipation. Comparatively, with other clustering protocols, our proposed methods reveal an enhanced network lifetime with an improved network throughput and adaptability based on selected standard metric of performance measurement.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140492368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dasheng Chen, Qi Song, Yinbin Zhang, Ling Li, Zhiming Yang
{"title":"Comparative Analysis of Time Series Prediction Algorithms on Multiple Network Function Data of NWDAF","authors":"Dasheng Chen, Qi Song, Yinbin Zhang, Ling Li, Zhiming Yang","doi":"10.1155/2024/5525561","DOIUrl":"https://doi.org/10.1155/2024/5525561","url":null,"abstract":"With the emergence and vigorous development of 5G technology, there is a significant surge in network usage and traffic, resulting in heightened complexity within network and IT environments. This exponential increase in activity produces a plethora of events, making conventional systems inadequate for the efficient management of 5G networks. In comparison to 4G technology, 5G technology brings forth a host of new features, one of which is the network data analytics function (NWDAF). This function grants network operators the flexibility to either employ their own data analytics methodologies based on machine learning (ML) and deep learning (DL) into their networks. In this paper, we present a dataset named “NWDAF-NFPP” for network function performance time series prediction, collected from a laboratory at China Telecom. The dataset is carefully anonymized to ensure maximum realism and comprehensiveness, while safeguarding sensitive information. It encompasses eight categories of network functions, with data collected at five-minute intervals. The availability of this dataset provides valuable resources for researchers to conduct time series prediction research on network element performance. Following data collection, a total of six models were employed for network element performance prediction, encompassing both machine learning and deep learning approaches. This diverse set of models was carefully chosen to ensure comprehensive coverage of different techniques and algorithms. Through the comparison and analysis of these models, we aim to evaluate their predictive capabilities and identify the most effective approach for network element performance prediction. This comparative analysis will provide valuable insights into the strengths and limitations of each model, aiding in informed decision-making for network optimization and management strategies in the future.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140508900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lina Yuan, Huajun Chen, Anran Zhou, Rong Wang, Xianli Wen
{"title":"Multiantenna Clustering Collaboration for WPCNs Based on Nonlinear EH","authors":"Lina Yuan, Huajun Chen, Anran Zhou, Rong Wang, Xianli Wen","doi":"10.1155/2023/9948725","DOIUrl":"https://doi.org/10.1155/2023/9948725","url":null,"abstract":"This article considers a wireless-powered communication network (WPCN) composed of a multiantenna hybrid access point (HAP) based on nonlinear energy harvesting (EH). To improve some distant WDs’ throughput performance, one of them is allowed to be selected as a cluster head (CH) to help transfer information from other cluster members (CMs). Nevertheless, the proposed clustering collaboration’s performance is essentially restricted by the CH’s energy-intensive consumption (EC), which requires to transfer every WDs’ information, covering its own. In order to figure out the question, the HAP’s energy beamforming (EB) capability with multiple antennas is utilized that can concentrate greater transmission power into the CH to equilibrate its EC to assist other WDs. To be specific, each WD’s throughput performance is firstly derived under the proposed approach. A high-efficiency optimization algorithm for addressing cooperative optimization problem is put forward. In addition, the simulations are carried out in the actual network environment, and the results demonstrate that our proposed clustering collaboration with multiple antennas can validly enhance the WPCN’s throughput fairness based on nonlinear EH.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cognitive Radio Spectrum Sensing-Based QAM Technique Using Blockchain","authors":"D. Balakumar, S. Nandakumar","doi":"10.1155/2023/7225260","DOIUrl":"https://doi.org/10.1155/2023/7225260","url":null,"abstract":"Cognitive radio (CR) is a novel concept developed to solve concerns such as spectrum underutilization and scarcity. Spectrum detection methods are employed in the blockchain-based CR to make optimum use of the spectrum reserves. In this paper, an attempt is made to evaluate the effectiveness of an energy sensor using collaborative spectrum detection. Wideband is defined as the frequency range between 470 MHz and 790 MHz, and additive white Gaussian noise (AWGN) is employed. The probability of detection ( <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>d</mtext> </mrow> </msub> </math> ) under different situations is examined using detection in the receiver operational curve (ROC). According to the findings, the <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\"> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>d</mtext> </mrow> </msub> </math> increases with the number of samples. This form of sensing, which is thought to be the easiest and best, uses energy-detecting spectrum sensing. To address ambiguity, the M-ary QAM technique is provided, which increases aggregate effectiveness in terms of the percentage of false alarm ( <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\"> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>f</mtext> </mrow> </msub> </math> ) and probability of missed detection ( <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M4\"> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>m</mtext> </mrow> </msub> </math> ) by 5% at a comparable delay period. When CR encounters shadowing and impacts situations, the client cannot tell the difference between an underutilized zone and fading. In comparison to the existing model, this study increases the likelihood of detecting a 3 dBm SNR for a 64-QAM modulated signal by at least 15%.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135510906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sum Rate Optimization for MIMO Multicasting Network with Active IRS","authors":"Ping Li, Jinhong Bian","doi":"10.1155/2023/5903661","DOIUrl":"https://doi.org/10.1155/2023/5903661","url":null,"abstract":"This paper considers a multiple-input multiple-output (MIMO) multicasting system aided by the intelligent reflecting surface (IRS). We aim to maximize the sum information rate via jointly designing the transmit precoding matrix and the reflecting coefficient (RC) matrix, subject to the transmit power constrains of the Tx and IRS. To tackle the nonconvex problem, we recast the original problem into an equivalent formulation by using some important facts about matrices and proposed a block coordinate descent (BCD) method to optimize the variables. Finally, simulation results validate the effectiveness of active IRS in enhancing the rate performance.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136062720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ishimwe Viviane, Emmanuel Masabo, Habiyaremye Joseph, Mitsindo Rene, Elias Bizuru
{"title":"IoT-Based Real-Time Crop Drying and Storage Monitoring System","authors":"Ishimwe Viviane, Emmanuel Masabo, Habiyaremye Joseph, Mitsindo Rene, Elias Bizuru","doi":"10.1155/2023/4803000","DOIUrl":"https://doi.org/10.1155/2023/4803000","url":null,"abstract":"Maize flour obtained from the dried corn is one of the most consumed foods in Rwanda. It is imperative that this should be healthy and risk-free for a safe consumption. Therefore, it is vital to keep track of the environmental conditions during the drying process and the characteristics that exist inside maize storage containers. In Rwanda, traditional methods are most commonly used by maize farmers for drying and storage purposes, where no smart system is being used to monitor the environmental conditions under which the maize grains are dried and stored. This mostly affects the quality of maize and flour being produced which will finally affect food security. In this research, temperature, humidity, and light sensors are deployed in the grain storage containers for environmental parameter detection purposes to achieve the primary goal of providing practical, secure, and easily accessible storage in inclement weather. Temperature and humidity are two factors that have an impact on grain quality while in storage. The ThingSpeak platform has been used to help farmers monitor the drying and storing conditions of the maize on a real-time basis. A global system for mobile (GSM) communication module is used to notify farmers by sending a short message in case of critical drying or storing environmental parameters under which the maize grains are stored. The result is shown in the form of humidity, temperature, and light graphs which are displayed on the ThingSpeak platform in real-time mode.","PeriodicalId":54327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134885111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}