Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065896
Qingyang Chen, Z. Qiang, Hong Lin
Super-resolution (SR) is the process of restoring a limited number of low-resolution (LR) images to high-resolution (HR) images. In recent years, with the vigorous development of deep learning in computer vision, its applications in image super resolution have also made significant progress. In this paper we aim to integrate and analyze the existing deep-learning based image super-resolution models, and show several models with the best performance. We divide the models into five main categories based on where the sampling is located in the different models. Then we analyze and compare the different networks architectures. We also list some tips which are effective in super-resolution networks. At the end of this paper, we analyze the existing problems of super-resolution based on deep learning and make an outlook on the future of super-resolution development.
{"title":"A Review of Super Resolution Based on Deep Learning","authors":"Qingyang Chen, Z. Qiang, Hong Lin","doi":"10.1109/ICCC56324.2022.10065896","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065896","url":null,"abstract":"Super-resolution (SR) is the process of restoring a limited number of low-resolution (LR) images to high-resolution (HR) images. In recent years, with the vigorous development of deep learning in computer vision, its applications in image super resolution have also made significant progress. In this paper we aim to integrate and analyze the existing deep-learning based image super-resolution models, and show several models with the best performance. We divide the models into five main categories based on where the sampling is located in the different models. Then we analyze and compare the different networks architectures. We also list some tips which are effective in super-resolution networks. At the end of this paper, we analyze the existing problems of super-resolution based on deep learning and make an outlook on the future of super-resolution development.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129608775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065789
Yongqiang Wang, Di Zhang, Ning Liu, Q. Wan
Target self-occlusion and view limitation of scanning equipment will make boundary and hole points exist in 3D point cloud data. The detection of boundary and hole points is an essential processing step for many related applications, such as the repair of point cloud holes. In this paper, we propose a unified detection algorithm for the point cloud's boundary and hole points. First, the algorithm utilizes the point cloud resolution to define a spherical neighbourhood and establishes the covariance matrix through neighbours. Then, we analyze the covariance matrix and invoke the angle criterion to judge whether the data point is a boundary point. The experimental results are carried out, which indicates that the proposed approach is superior to the comparative methods in time consumption and the success rate of boundary point detection. Furthermore, it is also robust to changes in geometric structure and the number of holes in the point cloud.
{"title":"A Unified Detection Method of Boundary and Hole Points Based on Point Cloud Resolution","authors":"Yongqiang Wang, Di Zhang, Ning Liu, Q. Wan","doi":"10.1109/ICCC56324.2022.10065789","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065789","url":null,"abstract":"Target self-occlusion and view limitation of scanning equipment will make boundary and hole points exist in 3D point cloud data. The detection of boundary and hole points is an essential processing step for many related applications, such as the repair of point cloud holes. In this paper, we propose a unified detection algorithm for the point cloud's boundary and hole points. First, the algorithm utilizes the point cloud resolution to define a spherical neighbourhood and establishes the covariance matrix through neighbours. Then, we analyze the covariance matrix and invoke the angle criterion to judge whether the data point is a boundary point. The experimental results are carried out, which indicates that the proposed approach is superior to the comparative methods in time consumption and the success rate of boundary point detection. Furthermore, it is also robust to changes in geometric structure and the number of holes in the point cloud.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128307956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065998
Wang Lan, Guan Lian
Employee green behavior is a key driver of sustainable competitive advantage. Many academic scholars and practical managers explore how to promote employee green behavior. In the context of carbon peak and carbon neutrality, more and more enterprises are carrying out green transformation strategy. Employee green behavior also plays an important role in this process. This paper elaborates a theoretical framework that relates mindfulness to employee green behavior. We argue organizational identification plays a prominent mediating role in enhancing employee green behavior. Using survey data from a sample of 211 employees, we demonstrated that mindfulness has a positive impact on employee green behavior through organizational identification. Theoretical and managerial implications are discussed.
{"title":"Study on the Impact of Mindfulness on Employee Green Behavior","authors":"Wang Lan, Guan Lian","doi":"10.1109/ICCC56324.2022.10065998","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065998","url":null,"abstract":"Employee green behavior is a key driver of sustainable competitive advantage. Many academic scholars and practical managers explore how to promote employee green behavior. In the context of carbon peak and carbon neutrality, more and more enterprises are carrying out green transformation strategy. Employee green behavior also plays an important role in this process. This paper elaborates a theoretical framework that relates mindfulness to employee green behavior. We argue organizational identification plays a prominent mediating role in enhancing employee green behavior. Using survey data from a sample of 211 employees, we demonstrated that mindfulness has a positive impact on employee green behavior through organizational identification. Theoretical and managerial implications are discussed.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128251828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065711
Zhengyang Huang, Xuyan Song, Yifan Luo, Jun Yang, Baojiang Cui
The Linux operating system is now extensively used on personal computers, cloud platforms, and enterprise servers. The security of the Linux kernel has also increased in importance. Several techniques, such as symbolic execution, data flow analysis, and reinforcement learning, have been adapted for vulnerability discovery in recent years. Among these techniques, fuzzing is the most widely used one. However, the ease of accessing each kernel code basic block has not been considered in previous research. This means many high-risk vulnerabilities cannot be detected. To solve this problem, we present Syzballer, a hybrid fuzzer that combines multi-armed bandits with basic block weight, which is calculated by traversing the control flow graph generated by the kernel source code. First, we compile the kernel source code into LLVM bitcode and use the static analysis tool SVF to compute the weight of each basic block. Then we launched the fuzzer and loaded the weight file. Finally, a multi-armed bandit machine model is used to dynamically alter the task and seed selection. To verify the effectiveness of Syzballer, we compared it with the two most popular kernel fuzzers, Syzkaller and Syzvegas. Experiments have demonstrated that our Syzballer has improved in terms of code coverage and vulnerability detection.
{"title":"Syzballer: Kernel Fuzzing Based on Basic Block Weight and Multi-armed Bandit","authors":"Zhengyang Huang, Xuyan Song, Yifan Luo, Jun Yang, Baojiang Cui","doi":"10.1109/ICCC56324.2022.10065711","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065711","url":null,"abstract":"The Linux operating system is now extensively used on personal computers, cloud platforms, and enterprise servers. The security of the Linux kernel has also increased in importance. Several techniques, such as symbolic execution, data flow analysis, and reinforcement learning, have been adapted for vulnerability discovery in recent years. Among these techniques, fuzzing is the most widely used one. However, the ease of accessing each kernel code basic block has not been considered in previous research. This means many high-risk vulnerabilities cannot be detected. To solve this problem, we present Syzballer, a hybrid fuzzer that combines multi-armed bandits with basic block weight, which is calculated by traversing the control flow graph generated by the kernel source code. First, we compile the kernel source code into LLVM bitcode and use the static analysis tool SVF to compute the weight of each basic block. Then we launched the fuzzer and loaded the weight file. Finally, a multi-armed bandit machine model is used to dynamically alter the task and seed selection. To verify the effectiveness of Syzballer, we compared it with the two most popular kernel fuzzers, Syzkaller and Syzvegas. Experiments have demonstrated that our Syzballer has improved in terms of code coverage and vulnerability detection.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128682730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065613
Juniie Chen, Yaiuan Wu
In underwater photography, the absorption and scattering of light may probably cause low contrast, blurred images, and color cast. We present an effective method for improving the quality of underwater images that have been degraded by medium scattering and absorption. It combines color compensation with multi-scale image fusion. Color compensation consists of independently correcting the value of $mathbf{R}$ channel and G-B channel of the input image and adjusting the white balance of the corrected image. After color compensation, the color of degraded image is restored effectively, but the blurring of image edges and details receiving scattering effects cannot be remedied. This problem can be solved by multi-scale image fusion. In our method, we use Gaussian pyramid and Laplace pyramid images for fusion, and these two feature pyramids are constructed by using the image after the illumination adjustment. The experimental results illustrate that dark-area sensitivity, global contrast, and edge sharpness of images have been improved by our methods. Moreover, in terms of visual effects and assessment metrics of underwater images, our method excels over other methods.
{"title":"Improved Color Balance and Fusion for Enhancement of Underwater Image","authors":"Juniie Chen, Yaiuan Wu","doi":"10.1109/ICCC56324.2022.10065613","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065613","url":null,"abstract":"In underwater photography, the absorption and scattering of light may probably cause low contrast, blurred images, and color cast. We present an effective method for improving the quality of underwater images that have been degraded by medium scattering and absorption. It combines color compensation with multi-scale image fusion. Color compensation consists of independently correcting the value of $mathbf{R}$ channel and G-B channel of the input image and adjusting the white balance of the corrected image. After color compensation, the color of degraded image is restored effectively, but the blurring of image edges and details receiving scattering effects cannot be remedied. This problem can be solved by multi-scale image fusion. In our method, we use Gaussian pyramid and Laplace pyramid images for fusion, and these two feature pyramids are constructed by using the image after the illumination adjustment. The experimental results illustrate that dark-area sensitivity, global contrast, and edge sharpness of images have been improved by our methods. Moreover, in terms of visual effects and assessment metrics of underwater images, our method excels over other methods.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129320531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065818
Tao Yan, Wenjun Hou
As the network grows in popularity, so does the popularity of network novels based on the network platform. Simultaneously, the network novel platform has amassed a huge number of network novels with unique network reviews-“Benzhangshuo”. The purpose of this article is to use text emotional analysis technology to extract and visualize emotional information in the main text and “Benzhangshuo”, as well as to assess their properties and their relationship. It can make recommendations for content development, retrieval channels, and network innovative recommendations. This study divides the emotion types in the network novel text and “Benzhangshuo” using an emotion analysis method based on an emotion dictionary. The experimental results demonstrate that the main text and “Benzhangshuo” in the popular novel Da Wang Rao Ming” have essentially the same emotion distribution principles, but the proportion of the two emotion distribution is different.
{"title":"Emotional Analysis and Comparison of Network Novel Review and Main Text","authors":"Tao Yan, Wenjun Hou","doi":"10.1109/ICCC56324.2022.10065818","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065818","url":null,"abstract":"As the network grows in popularity, so does the popularity of network novels based on the network platform. Simultaneously, the network novel platform has amassed a huge number of network novels with unique network reviews-“Benzhangshuo”. The purpose of this article is to use text emotional analysis technology to extract and visualize emotional information in the main text and “Benzhangshuo”, as well as to assess their properties and their relationship. It can make recommendations for content development, retrieval channels, and network innovative recommendations. This study divides the emotion types in the network novel text and “Benzhangshuo” using an emotion analysis method based on an emotion dictionary. The experimental results demonstrate that the main text and “Benzhangshuo” in the popular novel Da Wang Rao Ming” have essentially the same emotion distribution principles, but the proportion of the two emotion distribution is different.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124594058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065804
Y. Mao, Shizhan Cheng, Xingcheng Liu, En Zou
In recent years, neural network-based BP decoders for polar codes have draw much attention, due to their faster convergence and better error-correction performance compared with conventional BP decoders. However, the prior neural BP decoders have high storage cost and training complexity due to massive number of training weights, and the performance improvement is slight. In this work, we first propose a 2D-MSMS algorithm with a shared weight scheme, in which the nodes in the same layer share a weight among different iterations. These learnable weights are optimized by deep learning techniques. Then, we propose a CRC-Aided relaxed 2D-MSMS polar de-coder by introducing relaxation method and CRC-Aided early termination scheme. Simulation results show that our proposed decoder can effectively improve BER performance at medium to high SNR and reduce the amount of training weights by more than 95%.
{"title":"A Low Complexity Neural Network-Based BP Decoder for Polar Codes","authors":"Y. Mao, Shizhan Cheng, Xingcheng Liu, En Zou","doi":"10.1109/ICCC56324.2022.10065804","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065804","url":null,"abstract":"In recent years, neural network-based BP decoders for polar codes have draw much attention, due to their faster convergence and better error-correction performance compared with conventional BP decoders. However, the prior neural BP decoders have high storage cost and training complexity due to massive number of training weights, and the performance improvement is slight. In this work, we first propose a 2D-MSMS algorithm with a shared weight scheme, in which the nodes in the same layer share a weight among different iterations. These learnable weights are optimized by deep learning techniques. Then, we propose a CRC-Aided relaxed 2D-MSMS polar de-coder by introducing relaxation method and CRC-Aided early termination scheme. Simulation results show that our proposed decoder can effectively improve BER performance at medium to high SNR and reduce the amount of training weights by more than 95%.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124696523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065870
Hui Yang, Yang Cao
With the rapid development of big data and AI technologies, the sharing and opening-up, development and utilization of big data from government, medical becomes into one of our priorities. However, a problem that has puzzled us for a long time is that, the usage rate of massive unstructured multi-modal data as an absolute main body is still very low, which seriously restricts the circulation of data factors and faces the increasingly serious challenge of security-compliance. To speed up the circulation process and value release of data factors, this paper proposed a security-compliant and lightweight cloud computing model for massive unstructured multi-modal data. The implementation method includes multi-modal feature recognition and extraction from unstructured big data with NLP, CNN, image processing, audio processing technologies, fast and safe cipher-text calculation, and cipher-text retrieval with HE (homomorphic encryption) against the feature index database, and multi-modal data fusion, etc. With the above model & algorithms including the optimization solution of the HE algorithm, we verified the “compute-able but invisible” of massive cross-media unstructured data, and proved the security, validity, and time efficiency.
{"title":"Research on Cloud Computing Security & Privacy Protection of Massive Unstructured Multi-Modal Data","authors":"Hui Yang, Yang Cao","doi":"10.1109/ICCC56324.2022.10065870","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065870","url":null,"abstract":"With the rapid development of big data and AI technologies, the sharing and opening-up, development and utilization of big data from government, medical becomes into one of our priorities. However, a problem that has puzzled us for a long time is that, the usage rate of massive unstructured multi-modal data as an absolute main body is still very low, which seriously restricts the circulation of data factors and faces the increasingly serious challenge of security-compliance. To speed up the circulation process and value release of data factors, this paper proposed a security-compliant and lightweight cloud computing model for massive unstructured multi-modal data. The implementation method includes multi-modal feature recognition and extraction from unstructured big data with NLP, CNN, image processing, audio processing technologies, fast and safe cipher-text calculation, and cipher-text retrieval with HE (homomorphic encryption) against the feature index database, and multi-modal data fusion, etc. With the above model & algorithms including the optimization solution of the HE algorithm, we verified the “compute-able but invisible” of massive cross-media unstructured data, and proved the security, validity, and time efficiency.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130496303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065990
Yong Zhang, W. Chen, Ying Zang
Fine-grained visual classification (FGVC) is to identify subcategories with very small differences from image data with large intra-class differences and small inter-class differences. It is a very challenging task in the field of computer vision. With the rapid development of deep learning, FGVC algorithms have developed from traditional strong supervised learning, which relies on a large amount of manual annotation information, to weakly supervised learning. Weakly supervised learning includes algorithms based on traditional deep convolutional neural networks and based on vision transformer (ViT). In recent years, ViT has shown strong performance in FGVC and tends to surpass deep convolutional neural networks. This paper first introduces the purpose and characteristics of fine-grained image classification tasks, then introduces the corresponding public datasets and traditional convolutional network-based algorithms, discusses the performance of ViT-based algorithms and their advantages and disadvantages, and finally summarizes these algorithms.
{"title":"Fine-Grained Vision Categorization with Vision Transformer: A Survey","authors":"Yong Zhang, W. Chen, Ying Zang","doi":"10.1109/ICCC56324.2022.10065990","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065990","url":null,"abstract":"Fine-grained visual classification (FGVC) is to identify subcategories with very small differences from image data with large intra-class differences and small inter-class differences. It is a very challenging task in the field of computer vision. With the rapid development of deep learning, FGVC algorithms have developed from traditional strong supervised learning, which relies on a large amount of manual annotation information, to weakly supervised learning. Weakly supervised learning includes algorithms based on traditional deep convolutional neural networks and based on vision transformer (ViT). In recent years, ViT has shown strong performance in FGVC and tends to surpass deep convolutional neural networks. This paper first introduces the purpose and characteristics of fine-grained image classification tasks, then introduces the corresponding public datasets and traditional convolutional network-based algorithms, discusses the performance of ViT-based algorithms and their advantages and disadvantages, and finally summarizes these algorithms.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123937393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065770
Xu Dong, Piming Ma, Lei Zhang, Lu Zhang
In this paper, we study the low-cost and high-speed information services for users at the sea and low-latency information services for vehicle-to-vehicle(V2V) users near the shore. We formulate the power allocation and relay design problem as a power minimization problem while fulfilling the rate constraints of both vessel users and vehicular users additionally with the low-latency requirement of the vehicular users. Using the Lyapunov optimization theory, the original problem is first transformed to a Lyapunov-drift-plus-penalty minimization problem. Then, an iterative algorithm is proposed to decompose the original problem into two non-convex sub-problems, while the sub-problem 1 can be solved using the feasible point pursuit successive convex approximation(FPP-SCA) algorithm and the sub-problem 2 can be solved by the SCA and the Lagrangian dual method. Finally, simulation results show that our proposed algorithm is beneficial in energy efficiency while guaranteeing the quality-of-service(QoS) requirement of vessel users and vehicular users.
{"title":"Joint Power Allocation and Relay Design for Low-Latency and Energy-efficiency Ground-Ocean Network","authors":"Xu Dong, Piming Ma, Lei Zhang, Lu Zhang","doi":"10.1109/ICCC56324.2022.10065770","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065770","url":null,"abstract":"In this paper, we study the low-cost and high-speed information services for users at the sea and low-latency information services for vehicle-to-vehicle(V2V) users near the shore. We formulate the power allocation and relay design problem as a power minimization problem while fulfilling the rate constraints of both vessel users and vehicular users additionally with the low-latency requirement of the vehicular users. Using the Lyapunov optimization theory, the original problem is first transformed to a Lyapunov-drift-plus-penalty minimization problem. Then, an iterative algorithm is proposed to decompose the original problem into two non-convex sub-problems, while the sub-problem 1 can be solved using the feasible point pursuit successive convex approximation(FPP-SCA) algorithm and the sub-problem 2 can be solved by the SCA and the Lagrangian dual method. Finally, simulation results show that our proposed algorithm is beneficial in energy efficiency while guaranteeing the quality-of-service(QoS) requirement of vessel users and vehicular users.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124238416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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