Pub Date : 2023-09-22DOI: 10.13052/jicts2245-800X.1132
Garsha Rostami
In computer systems security, role-based access control (RBAC) or role-based security is an approach to restricting system access to authorized users [1]. This paper will describe how the Kubernetes RBAC authorization sub-system works, how to leverage it to secure access to resources in the cluster, and how to validate the set policies through impersonation to ensure users and service accounts are granted the intended rights.
{"title":"Role-Based Access Control (RBAC) Authorization in Kubernetes","authors":"Garsha Rostami","doi":"10.13052/jicts2245-800X.1132","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1132","url":null,"abstract":"In computer systems security, role-based access control (RBAC) or role-based security is an approach to restricting system access to authorized users [1]. This paper will describe how the Kubernetes RBAC authorization sub-system works, how to leverage it to secure access to resources in the cluster, and how to validate the set policies through impersonation to ensure users and service accounts are granted the intended rights.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 3","pages":"237-260"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255391/10255393.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68142148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.13052/jicts2245-800X.1133
Xinyuan Tian;Bingqin Pan;Liping Bai;Guangbin Wang;Deyun Mo
In the era of Industry 4.0, digital agriculture is developing very rapidly and has achieved considerable results. Nowadays, digital agriculture-based research is more focused on the use of robotic fruit picking technology, and the main research direction of such topics is algorithms for computer vision. However, when computer vision algorithms successfully locate the target object, it is still necessary to use robotic arm movement to reach the object at the physical level, but such path planning has received minimal attention. Based on this research deficiency, we propose to use Unity software as a digital twin platform to plan the robotic arm path and use ML-Agent plug-in as a reinforcement learning means to train the robotic arm path, to improve the accuracy of the robotic arm to reach the fruit, and happily the effect of this method is much improved than the traditional method.
{"title":"Fruit Picking Robot Arm Training Solution Based on Reinforcement Learning in Digital Twin","authors":"Xinyuan Tian;Bingqin Pan;Liping Bai;Guangbin Wang;Deyun Mo","doi":"10.13052/jicts2245-800X.1133","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1133","url":null,"abstract":"In the era of Industry 4.0, digital agriculture is developing very rapidly and has achieved considerable results. Nowadays, digital agriculture-based research is more focused on the use of robotic fruit picking technology, and the main research direction of such topics is algorithms for computer vision. However, when computer vision algorithms successfully locate the target object, it is still necessary to use robotic arm movement to reach the object at the physical level, but such path planning has received minimal attention. Based on this research deficiency, we propose to use Unity software as a digital twin platform to plan the robotic arm path and use ML-Agent plug-in as a reinforcement learning means to train the robotic arm path, to improve the accuracy of the robotic arm to reach the fruit, and happily the effect of this method is much improved than the traditional method.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 3","pages":"261-282"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255391/10255409.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68142149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.13052/jicts2245-800X.1135
Jiao Tang
This paper aims to use the improved Generative Adversarial Network (GAN) model for Three Dimensional (3D) animation graphic design, improve the efficiency of 3D animation graphic design, and promote the accuracy of model recognition. It acquires 3D animated scene color images from different perspectives. This paper performs 3D visualization through point clouds, outputs high-quality point cloud results, and uses Convolutional Neural Network (CNN), Earth-Mover (EM) distance, and Least Squares Method (LSM) to improve the GAN model. Finally, the effectiveness of the improved GAN in the graphic design of 3D animation scenes and the effects of different improved models in generating 3D animation scene images are analyzed. The results show that the computational loss amplitude of the improved GAN model using Label Smoothing processing deep convolutional neural network is between [2], [3]. The generator loss variation is smaller, and the image quality of the generated 3D animation scene is gradually improved. The training process of the LSM-improved model is more stable, and the loss value is lower than that of the EM distance improved model. The loss value of the generator is [0.3,0.5], and the loss value of the discriminator is [0.1,0.2]. The Inception score of the LSM-improved model is 0.0297 higher than that of the CNN-improved model and the EM distance improved model and 0.0198 higher than that of the GAN model.
{"title":"Graphic Design of 3D Animation Scenes Based on Deep Learning and Information Security Technology","authors":"Jiao Tang","doi":"10.13052/jicts2245-800X.1135","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1135","url":null,"abstract":"This paper aims to use the improved Generative Adversarial Network (GAN) model for Three Dimensional (3D) animation graphic design, improve the efficiency of 3D animation graphic design, and promote the accuracy of model recognition. It acquires 3D animated scene color images from different perspectives. This paper performs 3D visualization through point clouds, outputs high-quality point cloud results, and uses Convolutional Neural Network (CNN), Earth-Mover (EM) distance, and Least Squares Method (LSM) to improve the GAN model. Finally, the effectiveness of the improved GAN in the graphic design of 3D animation scenes and the effects of different improved models in generating 3D animation scene images are analyzed. The results show that the computational loss amplitude of the improved GAN model using Label Smoothing processing deep convolutional neural network is between [2], [3]. The generator loss variation is smaller, and the image quality of the generated 3D animation scene is gradually improved. The training process of the LSM-improved model is more stable, and the loss value is lower than that of the EM distance improved model. The loss value of the generator is [0.3,0.5], and the loss value of the discriminator is [0.1,0.2]. The Inception score of the LSM-improved model is 0.0297 higher than that of the CNN-improved model and the EM distance improved model and 0.0198 higher than that of the GAN model.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 3","pages":"307-328"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255391/10255410.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68142150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.13052/jicts2245-800X.1123
Xiao Zhou;Songlin Yu;Jijun Wang;Yuhua Chen;Fangyuan Li;Yan Li
Image data with different spectral features contain different attribute information of a target, which is naturally complementary and can provide more comprehensive and detailed features after registration and fusion. Image registration methods based on point features have the advantages of high speed and precision, and have been widely used in visible light image registration. For registration of multiscale images and those with different spectral characteristics, the precision of these methods is affected by such factors as complex gradient variation. To this end, we add a spatial constraint model to point feature image registration, and improve the method from the aspects of feature point selection, registration, and image conversion parameter calculation. The method is applied to different types of image registration programs, and the results show that it can effectively improve the registration accuracy of multiscale images with different spectral characteristics.
{"title":"Adaptive Feature Point Image Registration Algorithm with Added Spatial Constraint Model","authors":"Xiao Zhou;Songlin Yu;Jijun Wang;Yuhua Chen;Fangyuan Li;Yan Li","doi":"10.13052/jicts2245-800X.1123","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1123","url":null,"abstract":"Image data with different spectral features contain different attribute information of a target, which is naturally complementary and can provide more comprehensive and detailed features after registration and fusion. Image registration methods based on point features have the advantages of high speed and precision, and have been widely used in visible light image registration. For registration of multiscale images and those with different spectral characteristics, the precision of these methods is affected by such factors as complex gradient variation. To this end, we add a spatial constraint model to point feature image registration, and improve the method from the aspects of feature point selection, registration, and image conversion parameter calculation. The method is applied to different types of image registration programs, and the results show that it can effectively improve the registration accuracy of multiscale images with different spectral characteristics.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 2","pages":"157-174"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255407/10255435.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68097862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.13052/jicts2245-800X.1134
Yan Meng;Jungjin Kim;Hak-chun Lee;Cho Dong Je;Peiyun Cheng
This study aims to analyze the application of information security (IS) technology and blockchain in the media economy, and the impact of cross-border cooperation and value chain reconstruction combined with blockchain technology (BCT) on promoting innovation and digital transformation in the media economy. This study delves into the interplay between cross-border collaboration, value chain reconstruction, and BCT. It constructs a media economic digital platform by amalgamating blockchain and cross-border value chain principles, subsequently evaluating and analyzing its performance. Findings indicate that the proposed model exhibits a reduced block propagation time and enhanced security performance, boasting a 5% improvement. The platform's latency remains stable at approximately 245 ms. Survey analysis reveals an agreement rate exceeding 57.94% across dimensions such as data mining, customer relationship management, and classification effectiveness, contributing to heightened user satisfaction. Consequently, this study offers valuable insights into user relationship security management within cross-border collaborations, shedding light on novel avenues for sustainable development and digital transformation in the realm of the media economy.
{"title":"Innovation and Digital Transformation of Media Economy Based on Information Security Technology","authors":"Yan Meng;Jungjin Kim;Hak-chun Lee;Cho Dong Je;Peiyun Cheng","doi":"10.13052/jicts2245-800X.1134","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1134","url":null,"abstract":"This study aims to analyze the application of information security (IS) technology and blockchain in the media economy, and the impact of cross-border cooperation and value chain reconstruction combined with blockchain technology (BCT) on promoting innovation and digital transformation in the media economy. This study delves into the interplay between cross-border collaboration, value chain reconstruction, and BCT. It constructs a media economic digital platform by amalgamating blockchain and cross-border value chain principles, subsequently evaluating and analyzing its performance. Findings indicate that the proposed model exhibits a reduced block propagation time and enhanced security performance, boasting a 5% improvement. The platform's latency remains stable at approximately 245 ms. Survey analysis reveals an agreement rate exceeding 57.94% across dimensions such as data mining, customer relationship management, and classification effectiveness, contributing to heightened user satisfaction. Consequently, this study offers valuable insights into user relationship security management within cross-border collaborations, shedding light on novel avenues for sustainable development and digital transformation in the realm of the media economy.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 3","pages":"283-306"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255391/10255392.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68142151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1115
Xiaogang Li;Di Su;Dongxu Chang;Jiajia Liu;Liwei Wang;Zhansheng Tian;Shuxuan Wang;Wei Sun
Since UAV aerial images are usually captured by UAVs at high altitudes with oblique viewing angles, the amount of data is large, and the spatial resolution changes greatly, so the information on small targets is easily lost during segmentation. Aiming at the above problems, this paper presents a semantic segmentation method for UAV images, which introduces a multi-scale feature extraction and fusion module based on the encoding-decoding framework. By combining multi-scale channel feature extraction and multi-scale spatial feature extraction, the network can focus more on certain feature layers and spatial regions when extracting features. Some invalid redundant features are eliminated and the segmentation results are optimized by introducing global context information to capture global information and detailed information. Moreover, one compares the proposed method with FCN-8s, MSDNet, and U-Net network models on the large-scale multi-class UAV dataset UAVid. The experimental results indicate that the proposed method has higher performance in both MIoU and MPA, with an overall improvement of 9.2% and 8.5%, respectively, and its prediction capability is more balanced for both large-scale and small-scale targets.
{"title":"Multi-scale Feature Extraction and Fusion Net: Research on UAVs Image Semantic Segmentation Technology","authors":"Xiaogang Li;Di Su;Dongxu Chang;Jiajia Liu;Liwei Wang;Zhansheng Tian;Shuxuan Wang;Wei Sun","doi":"10.13052/jicts2245-800X.1115","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1115","url":null,"abstract":"Since UAV aerial images are usually captured by UAVs at high altitudes with oblique viewing angles, the amount of data is large, and the spatial resolution changes greatly, so the information on small targets is easily lost during segmentation. Aiming at the above problems, this paper presents a semantic segmentation method for UAV images, which introduces a multi-scale feature extraction and fusion module based on the encoding-decoding framework. By combining multi-scale channel feature extraction and multi-scale spatial feature extraction, the network can focus more on certain feature layers and spatial regions when extracting features. Some invalid redundant features are eliminated and the segmentation results are optimized by introducing global context information to capture global information and detailed information. Moreover, one compares the proposed method with FCN-8s, MSDNet, and U-Net network models on the large-scale multi-class UAV dataset UAVid. The experimental results indicate that the proposed method has higher performance in both MIoU and MPA, with an overall improvement of 9.2% and 8.5%, respectively, and its prediction capability is more balanced for both large-scale and small-scale targets.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 1","pages":"97-116"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261466.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1114
Yin Ying;Zhihong Zhou;Quanhai Zhang
The development of fifth generation mobile communication (5G) technology and Internet of Things (IoT) has enabled more mobile terminals to access the network and generate huge amounts of information content. This will make it difficult for the traditional IP-based host-to-host model to cope with the demand for massive data transmission, making network congestion an increasingly serious problem. To cope with these problems, a new network architecture, the Information-Centric Networking (ICN), a content network with content caching as one of its most core functions, has emerged. In addition, in the era when 5G and future 6G networks gradually realize the interconnection of everything, the Information-Centric Internet of Things (IC-IoT) based on ICN architecture has emerged, and a large number of IoT devices can use ICN nodes as edge devices to realize collaborative caching. The caching capacity of IC-IoT is directly related to the transmission efficiency and capacity of the whole network, and the performance of IC-IoT caching capacity is the top priority of research in this field. To address the above issues, the research in this paper focuses on deploying blockchains in IC-IoT networks and using the consensus mechanism of custom blockchains to motivate ICN nodes and non-ICN nodes in the network to perform caching collaboratively, which in turn improves the caching capacity of the whole network. The main work of this paper has the following points. First, incentivize IC-IoT collaborative caching based on blockchain consensus mechanism: by deploying blockchain in IC-IoT, rewarding nodes that obtain bookkeeping rights to incentivize network-wide collaborative caching, and designing experiments to compare the caching capacity of the network before and after the incentive; second, improve DPoS consensus mechanism to incentivize collaborative caching: Experiments are designed to compare the incentive capacity of PoW consensus mechanism and improved DPoS consensus mechanism for IC-IoT network collaborative caching, and to select the consensus mechanism with better performance; third, the design and implementation of IC-IoT test bed: write ICN program to form ICN network from basic communication to multiple nodes, and then deploying blockchain on the network for subsequent extension studies. This thesis demonstrates the feasibility of using blockchain for IC-IoT network cache collaborative incentive, and proves that the blockchain incentive method in this paper can improve the throughput of IC-IoT network cache by building a test bed.
{"title":"Blockchain-based Collaborative Caching Mechanism for Information Center IoT","authors":"Yin Ying;Zhihong Zhou;Quanhai Zhang","doi":"10.13052/jicts2245-800X.1114","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1114","url":null,"abstract":"The development of fifth generation mobile communication (5G) technology and Internet of Things (IoT) has enabled more mobile terminals to access the network and generate huge amounts of information content. This will make it difficult for the traditional IP-based host-to-host model to cope with the demand for massive data transmission, making network congestion an increasingly serious problem. To cope with these problems, a new network architecture, the Information-Centric Networking (ICN), a content network with content caching as one of its most core functions, has emerged. In addition, in the era when 5G and future 6G networks gradually realize the interconnection of everything, the Information-Centric Internet of Things (IC-IoT) based on ICN architecture has emerged, and a large number of IoT devices can use ICN nodes as edge devices to realize collaborative caching. The caching capacity of IC-IoT is directly related to the transmission efficiency and capacity of the whole network, and the performance of IC-IoT caching capacity is the top priority of research in this field. To address the above issues, the research in this paper focuses on deploying blockchains in IC-IoT networks and using the consensus mechanism of custom blockchains to motivate ICN nodes and non-ICN nodes in the network to perform caching collaboratively, which in turn improves the caching capacity of the whole network. The main work of this paper has the following points. First, incentivize IC-IoT collaborative caching based on blockchain consensus mechanism: by deploying blockchain in IC-IoT, rewarding nodes that obtain bookkeeping rights to incentivize network-wide collaborative caching, and designing experiments to compare the caching capacity of the network before and after the incentive; second, improve DPoS consensus mechanism to incentivize collaborative caching: Experiments are designed to compare the incentive capacity of PoW consensus mechanism and improved DPoS consensus mechanism for IC-IoT network collaborative caching, and to select the consensus mechanism with better performance; third, the design and implementation of IC-IoT test bed: write ICN program to form ICN network from basic communication to multiple nodes, and then deploying blockchain on the network for subsequent extension studies. This thesis demonstrates the feasibility of using blockchain for IC-IoT network cache collaborative incentive, and proves that the blockchain incentive method in this paper can improve the throughput of IC-IoT network cache by building a test bed.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 1","pages":"67-96"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261471.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68101488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1112
Ronghu Zhou
For enhance running effectiveness efficiency of logistics carriage supervisory depended on wireless sensor network (WSN), a novel wireless sensor network optimized by improved bat algorithm is established. Firstly, working theory and system framework of WSN depended on logistics monitoring system are analyzed. Secondly, B-MAC protocol is used in proposed wireless sensor network, and corresponding models are established, and recovery ratio of wireless sensor network is defined, and node deployment optimization of wireless sensor network is constructed. Thirdly, the optimization algorithm of node deployment of WSN is designed based on amended bat algorithm, and analysis procedure of this algorithm is established. Finally, a simulation analysis is carried out, analysis results show that performance of proposed WSN logistics carriage supervisory based on improved bat algorithm is better, which has quicker convergence speed and higher convergence precision, and reliability of proposed WSN logistics carriage supervisory is improved, the energy consumption of sensor node data transmission is reduced, and the life of WSN is improved. Proposed WSN based on logistics carriage supervisory based on improved BA has higher coverage ratio and higher efficiency. Therefore proposed wireless sensor network based on logistics carriage supervisory based on improved bat algorithm can obtain better monitoring efficiency, which has prospect application view.
{"title":"Research on Efficiency Optimization of Logistics Vehicle Monitoring Model Based on Wireless Sensor Network","authors":"Ronghu Zhou","doi":"10.13052/jicts2245-800X.1112","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1112","url":null,"abstract":"For enhance running effectiveness efficiency of logistics carriage supervisory depended on wireless sensor network (WSN), a novel wireless sensor network optimized by improved bat algorithm is established. Firstly, working theory and system framework of WSN depended on logistics monitoring system are analyzed. Secondly, B-MAC protocol is used in proposed wireless sensor network, and corresponding models are established, and recovery ratio of wireless sensor network is defined, and node deployment optimization of wireless sensor network is constructed. Thirdly, the optimization algorithm of node deployment of WSN is designed based on amended bat algorithm, and analysis procedure of this algorithm is established. Finally, a simulation analysis is carried out, analysis results show that performance of proposed WSN logistics carriage supervisory based on improved bat algorithm is better, which has quicker convergence speed and higher convergence precision, and reliability of proposed WSN logistics carriage supervisory is improved, the energy consumption of sensor node data transmission is reduced, and the life of WSN is improved. Proposed WSN based on logistics carriage supervisory based on improved BA has higher coverage ratio and higher efficiency. Therefore proposed wireless sensor network based on logistics carriage supervisory based on improved bat algorithm can obtain better monitoring efficiency, which has prospect application view.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 1","pages":"27-44"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261470.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1111
Wei Han;Shenggang Wu
Recent studies have found the mapping relationship between channel state information used in commercial Wi-Fi devices and environmental changes in the indoor environment, which can be used for sensing purposes. With the advantages of low cost and wide deployment of Wi-Fi facilities, passive indoor tracking systems based on Wi-Fi have huge potential. This article proposes and builds a passive indoor tracking system using commercial Wi-Fi devices, which realizes the function of tracking the human body's trajectory in indoor environment. The system uses only commercial Wi-Fi devices. It processes the collected channel state information data by sending and receiving two pairs of Wi-Fi devices, and extract the movement information the messy data to obtain the trajectory of the human body. The system conducts a geometric feature analysis in the complex plane to obtain accurate displacement information, and utilize a fusion algorithm, combining the AoA (Angle of Arrival) information obtained by MUSIC algorithm, to obtain accurate human trajectory. In the experiment, the complex plane geometric feature analysis algorithm reaches centimeter-level accuracy in obtaining displacement information, while the system reaches decimeter-level accuracy on in obtaining indoor human trajectory on a simulation dataset.
{"title":"Passive Indoor Tracking Fusion Algorithm Using Commodity Wi-Fi","authors":"Wei Han;Shenggang Wu","doi":"10.13052/jicts2245-800X.1111","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1111","url":null,"abstract":"Recent studies have found the mapping relationship between channel state information used in commercial Wi-Fi devices and environmental changes in the indoor environment, which can be used for sensing purposes. With the advantages of low cost and wide deployment of Wi-Fi facilities, passive indoor tracking systems based on Wi-Fi have huge potential. This article proposes and builds a passive indoor tracking system using commercial Wi-Fi devices, which realizes the function of tracking the human body's trajectory in indoor environment. The system uses only commercial Wi-Fi devices. It processes the collected channel state information data by sending and receiving two pairs of Wi-Fi devices, and extract the movement information the messy data to obtain the trajectory of the human body. The system conducts a geometric feature analysis in the complex plane to obtain accurate displacement information, and utilize a fusion algorithm, combining the AoA (Angle of Arrival) information obtained by MUSIC algorithm, to obtain accurate human trajectory. In the experiment, the complex plane geometric feature analysis algorithm reaches centimeter-level accuracy in obtaining displacement information, while the system reaches decimeter-level accuracy on in obtaining indoor human trajectory on a simulation dataset.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 1","pages":"1-26"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261465.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.13052/jicts2245-800X.1113
Xiaoxia Li
Establishing an efficient cloud computing task scheduling model is the object of many scholars' research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization; we set thresholds for the radius of core fireworks and non-core fireworks for optimization; we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing.
{"title":"An IFWA-BSA Based Approach for Task Scheduling in Cloud Computing","authors":"Xiaoxia Li","doi":"10.13052/jicts2245-800X.1113","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1113","url":null,"abstract":"Establishing an efficient cloud computing task scheduling model is the object of many scholars' research. In view of the low scheduling efficiency in cloud computing task scheduling, we propose a cloud computing task scheduling algorithm based on the fusion of the Fireworks Algorithm and Bird Swarm Algorithm (IFWA-BSA). Firstly, we describe the cloud computing task scheduling model based on time and cost constraint functions, secondly, we use chaotic backward learning and Coasean distribution for optimization in FWA initialization; we set thresholds for the radius of core fireworks and non-core fireworks for optimization; we filter the IFWA individuals after each iteration by BSA algorithm, and finally, we use the IFWA-BSA algorithm is used in cloud computing task scheduling model to solve the optimal solution. In the simulation experiments, IFWA-BSA has obvious advantages over ACO, PSO and FWA in the comparison of execution time and consumption cost indexes, which reduces the scheduling time and cost of cloud computing.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"11 1","pages":"45-66"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10261463/10261464.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67954659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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