Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000074
Ce Yan, Yuanqing Xia, Hongjiu Yang, Yufeng Zhan
The industrial Internet of Things (IIoT) is a new industrial idea that combines the latest information and communication technologies with the industrial economy. In this paper, a cloud control structure is designed for IIoT in cloud-edge environment with three modes of 5G. For 5G based IIoT, the time sensitive network (TSN) service is introduced in transmission network. A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration. For a transmission control protocol (TCP) model with nonlinear disturbance, time delay and uncertainties, a robust adaptive fuzzy sliding mode controller (AFSMC) is given with control rule parameters. IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows. IIoT workflow scheduling is a non-deterministic polynomial (NP)-hard problem in cloud-edge environment. An adaptive and non-local-convergent particle swarm optimization (ANCPSO) is designed with nonlinear inertia weight to avoid falling into local optimum, which can reduce the makespan and cost dramatically. Simulation and experiments demonstrate that ANCPSO has better performances than other classical algorithms.
{"title":"Cloud Control for IIoT in a Cloud-Edge Environment","authors":"Ce Yan, Yuanqing Xia, Hongjiu Yang, Yufeng Zhan","doi":"10.23919/jsee.2024.000074","DOIUrl":"https://doi.org/10.23919/jsee.2024.000074","url":null,"abstract":"The industrial Internet of Things (IIoT) is a new industrial idea that combines the latest information and communication technologies with the industrial economy. In this paper, a cloud control structure is designed for IIoT in cloud-edge environment with three modes of 5G. For 5G based IIoT, the time sensitive network (TSN) service is introduced in transmission network. A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration. For a transmission control protocol (TCP) model with nonlinear disturbance, time delay and uncertainties, a robust adaptive fuzzy sliding mode controller (AFSMC) is given with control rule parameters. IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows. IIoT workflow scheduling is a non-deterministic polynomial (NP)-hard problem in cloud-edge environment. An adaptive and non-local-convergent particle swarm optimization (ANCPSO) is designed with nonlinear inertia weight to avoid falling into local optimum, which can reduce the makespan and cost dramatically. Simulation and experiments demonstrate that ANCPSO has better performances than other classical algorithms.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"394 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000071
Wei Liu, Yifeng Jin, Lei Zhang, Zihe Gao, Ying Tao
A dynamic multi-beam resource allocation algorithm for large low Earth orbit (LEO) constellation based on on-board distributed computing is proposed in this paper. The allocation is a combinatorial optimization process under a series of complex constraints, which is important for enhancing the matching between resources and requirements. A complex algorithm is not available because that the LEO on-board resources is limited. The proposed genetic algorithm (GA) based on two-dimensional individual model and uncorrelated single paternal inheritance method is designed to support distributed computation to enhance the feasibility of on-board application. A distributed system composed of eight embedded devices is built to verify the algorithm. A typical scenario is built in the system to evaluate the resource allocation process, algorithm mathematical model, trigger strategy, and distributed computation architecture. According to the simulation and measurement results, the proposed algorithm can provide an allocation result for more than 1 500 tasks in 14 s and the success rate is more than 91% in a typical scene. The response time is decreased by 40% compared with the conditional GA.
{"title":"Dynamic Access Task Scheduling of LEO Constellation Based on Space-Based Distributed Computing","authors":"Wei Liu, Yifeng Jin, Lei Zhang, Zihe Gao, Ying Tao","doi":"10.23919/jsee.2024.000071","DOIUrl":"https://doi.org/10.23919/jsee.2024.000071","url":null,"abstract":"A dynamic multi-beam resource allocation algorithm for large low Earth orbit (LEO) constellation based on on-board distributed computing is proposed in this paper. The allocation is a combinatorial optimization process under a series of complex constraints, which is important for enhancing the matching between resources and requirements. A complex algorithm is not available because that the LEO on-board resources is limited. The proposed genetic algorithm (GA) based on two-dimensional individual model and uncorrelated single paternal inheritance method is designed to support distributed computation to enhance the feasibility of on-board application. A distributed system composed of eight embedded devices is built to verify the algorithm. A typical scenario is built in the system to evaluate the resource allocation process, algorithm mathematical model, trigger strategy, and distributed computation architecture. According to the simulation and measurement results, the proposed algorithm can provide an allocation result for more than 1 500 tasks in 14 s and the success rate is more than 91% in a typical scene. The response time is decreased by 40% compared with the conditional GA.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"23 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000088
Qin Sun, Hongxu Li, Yifan Zeng, Yingchao Zhang
As the unmanned weap system-of systems (UWSoS) becomes complex, the inevitable uncertain interference gradually increases, which leads to a strong emphasis on the resilience of UWSoS. Hence, this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS. First, a unified resilience-driven cooperative reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement. Subsequently, a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence, combining the cooperative pair resilience contribution index (CPRCI) and cooperative pair importance index (CPII). At last, the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include different attack modes and intensities. The analysis results can provide a reference for decision-makers to manage UWSoS.
{"title":"Resilience-Driven Cooperative Reconfiguration Strategy for Unmanned Weapon System-of-Systems","authors":"Qin Sun, Hongxu Li, Yifan Zeng, Yingchao Zhang","doi":"10.23919/jsee.2024.000088","DOIUrl":"https://doi.org/10.23919/jsee.2024.000088","url":null,"abstract":"As the unmanned weap system-of systems (UWSoS) becomes complex, the inevitable uncertain interference gradually increases, which leads to a strong emphasis on the resilience of UWSoS. Hence, this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS. First, a unified resilience-driven cooperative reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement. Subsequently, a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence, combining the cooperative pair resilience contribution index (CPRCI) and cooperative pair importance index (CPII). At last, the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include different attack modes and intensities. The analysis results can provide a reference for decision-makers to manage UWSoS.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"8 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000086
Cong Xu, Zishu He, Haicheng Liu
Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection performance. This paper proposes a method to handle false alarms in heterogeneous change detection. A lightweight network of two channels is bulit based on the combination of convolutional neural network (CNN) and graph convolutional network (GCN). CNNs learn feature difference maps of multitemporal images, and attention modules adaptively fuse CNN-based and graph-based features for different scales. GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels, generating change maps. Experimental evaluation on two datasets validates the efficacy of the proposed method in addressing false alarms.
{"title":"A Lightweight False Alarm Suppression Method in Heterogeneous Change Detection","authors":"Cong Xu, Zishu He, Haicheng Liu","doi":"10.23919/jsee.2024.000086","DOIUrl":"https://doi.org/10.23919/jsee.2024.000086","url":null,"abstract":"Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection performance. This paper proposes a method to handle false alarms in heterogeneous change detection. A lightweight network of two channels is bulit based on the combination of convolutional neural network (CNN) and graph convolutional network (GCN). CNNs learn feature difference maps of multitemporal images, and attention modules adaptively fuse CNN-based and graph-based features for different scales. GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels, generating change maps. Experimental evaluation on two datasets validates the efficacy of the proposed method in addressing false alarms.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"10 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The observation error model of the underwater acoustic positioning system is an important factor to influence the positioning accuracy of the underwater target. For the position inconsistency error caused by considering the underwater target as a mass point, as well as the observation system error, the traditional error model best estimation trajectory (EMBET) with little observed data and too many parameters can lead to the ill-condition of the parameter model. In this paper, a multi-station fusion system error model based on the optimal polynomial constraint is constructed, and the corresponding observation system error identification based on improved spectral clustering is designed. Firstly, the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization. Then a multi-station non-oriented graph network is established, which can address the problem of the inaccurate identification for the system errors. Moreover, the similarity matrix of the spectral clustering is improved, and the iterative identification for the system errors based on the improved spectral clustering is proposed. Finally, the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accurately identify the system errors, and moreover can improve the positioning accuracy for the underwater target positioning.
{"title":"System Error Iterative Identification for Underwater Positioning Based on Spectral Clustering","authors":"Yu Lu, Jiongqi Wang, Zhangming He, Haiyin Zhou, Yao Xing, Xuanying Zhou","doi":"10.23919/jsee.2024.000069","DOIUrl":"https://doi.org/10.23919/jsee.2024.000069","url":null,"abstract":"The observation error model of the underwater acoustic positioning system is an important factor to influence the positioning accuracy of the underwater target. For the position inconsistency error caused by considering the underwater target as a mass point, as well as the observation system error, the traditional error model best estimation trajectory (EMBET) with little observed data and too many parameters can lead to the ill-condition of the parameter model. In this paper, a multi-station fusion system error model based on the optimal polynomial constraint is constructed, and the corresponding observation system error identification based on improved spectral clustering is designed. Firstly, the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization. Then a multi-station non-oriented graph network is established, which can address the problem of the inaccurate identification for the system errors. Moreover, the similarity matrix of the spectral clustering is improved, and the iterative identification for the system errors based on the improved spectral clustering is proposed. Finally, the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accurately identify the system errors, and moreover can improve the positioning accuracy for the underwater target positioning.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"13 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000083
Ping Yang, Bing Xiao, Xin Chen, Yuntao Hao
The laser-guided bomb (LGB) is an air-to-ground precision-guided weapon that offers high hit rates, great power, and ease of use. LGBs are guided by semi-active laser ground-seeking technology, which means that atmospheric conditions can affect their accuracy. The spatial release region (SRR) of LGBs is difficult to calculate precisely, especially when there is a poor field of view. This can result in a lower real hit probability. To increase the hit probability of LGBs in tough atmospheric situations, a novel method for calculating the SRR has been proposed. This method is based on the transmittance model of the $1.06mu mathrm{m}$ laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker. Then, it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region. This method can determine the release region of LGBs based on flight test data such as instantaneous velocity, altitude, off-axis angle, and atmospheric visibility. By more effectively employing aircraft release conditions, atmospheric visibility and other factors, the SRR calculation method can improve LGB hit probability by 9.2%.
{"title":"Quantitative Method for Calculating Spatial Release Region for Laser-Guided Bomb","authors":"Ping Yang, Bing Xiao, Xin Chen, Yuntao Hao","doi":"10.23919/jsee.2024.000083","DOIUrl":"https://doi.org/10.23919/jsee.2024.000083","url":null,"abstract":"The laser-guided bomb (LGB) is an air-to-ground precision-guided weapon that offers high hit rates, great power, and ease of use. LGBs are guided by semi-active laser ground-seeking technology, which means that atmospheric conditions can affect their accuracy. The spatial release region (SRR) of LGBs is difficult to calculate precisely, especially when there is a poor field of view. This can result in a lower real hit probability. To increase the hit probability of LGBs in tough atmospheric situations, a novel method for calculating the SRR has been proposed. This method is based on the transmittance model of the <tex xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">$1.06mu mathrm{m}$</tex> laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker. Then, it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region. This method can determine the release region of LGBs based on flight test data such as instantaneous velocity, altitude, off-axis angle, and atmospheric visibility. By more effectively employing aircraft release conditions, atmospheric visibility and other factors, the SRR calculation method can improve LGB hit probability by 9.2%.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"14 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000048
Ai Gao, Shengnan Xu, Zichen Zhao, Haibin Shang, Rui Xu
To maintain the stability of the inter-satellite link for gravitational wave detection, an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed. Different from the traditional fault diagnosis optimization algorithms, the fault intelligent learning method proposed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong coupling nonlinearity. By constructing a two-layer learning network, the method enables efficient joint diagnosis of fault areas and fault parameters. The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s, and the fault diagnosis efficiency is improved by 99.8% compared with the traditional algorithm.
{"title":"Fault Diagnosis Method of Link Control System for Gravitational Wave Detection","authors":"Ai Gao, Shengnan Xu, Zichen Zhao, Haibin Shang, Rui Xu","doi":"10.23919/jsee.2024.000048","DOIUrl":"https://doi.org/10.23919/jsee.2024.000048","url":null,"abstract":"To maintain the stability of the inter-satellite link for gravitational wave detection, an intelligent learning monitoring and fast warning method of the inter-satellite link control system failure is proposed. Different from the traditional fault diagnosis optimization algorithms, the fault intelligent learning method proposed in this paper is able to quickly identify the faults of inter-satellite link control system despite the existence of strong coupling nonlinearity. By constructing a two-layer learning network, the method enables efficient joint diagnosis of fault areas and fault parameters. The simulation results show that the average identification time of the system fault area and fault parameters is 0.27 s, and the fault diagnosis efficiency is improved by 99.8% compared with the traditional algorithm.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"30 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000045
Chengxi Li, Fu Wang, Wei Yan, Yansong Cui, Xiaodong Fan, Guangyu Zhu, Yanxi Xie, Lixin Yang, Luming Zhou, Ran Zhao, Ning Wang
A low-Earth-orbit (LEO) satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking. However, the large variability of the geographic distribution of the Earth's population leads to an uneven service volume distribution of access service. Moreover, the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas. To enhance the forwarding capability of satellite networks, we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall. Then, we propose a multi-region cooperative traffic scheduling algorithm. The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding, significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding. This algorithm can utilize all the global satellite resources and improve the utilization of network resources. We model the cooperative multi-region scheduling of large-scale LEO satellites. Based on the model, we build a system testbed using OMNET++ to compare the proposed method with existing techniques. The simulations show that our proposed method can reduce the packet loss probability by 30% and improve the resource utilization ratio by 3.69%.
{"title":"Multi-Network-Region Traffic Cooperative Scheduling in Large-Scale LEO Satellite Networks","authors":"Chengxi Li, Fu Wang, Wei Yan, Yansong Cui, Xiaodong Fan, Guangyu Zhu, Yanxi Xie, Lixin Yang, Luming Zhou, Ran Zhao, Ning Wang","doi":"10.23919/jsee.2024.000045","DOIUrl":"https://doi.org/10.23919/jsee.2024.000045","url":null,"abstract":"A low-Earth-orbit (LEO) satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking. However, the large variability of the geographic distribution of the Earth's population leads to an uneven service volume distribution of access service. Moreover, the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas. To enhance the forwarding capability of satellite networks, we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall. Then, we propose a multi-region cooperative traffic scheduling algorithm. The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding, significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding. This algorithm can utilize all the global satellite resources and improve the utilization of network resources. We model the cooperative multi-region scheduling of large-scale LEO satellites. Based on the model, we build a system testbed using OMNET++ to compare the proposed method with existing techniques. The simulations show that our proposed method can reduce the packet loss probability by 30% and improve the resource utilization ratio by 3.69%.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"34 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000072
Sai Han, Ao Li, Dongyue Zhang, Bin Zhu, Zelin Wang, Guangquan Wang, Jie Miao, Hongbing Ma
With the rapid development of low-orbit satellite communication networks both domestically and internationally, space-terrestrial integrated networks will become the future development trend. For space and terrestrial networks with limited resources, the utilization efficiency of the entire space-terrestrial integrated networks resources can be affected by the core network indirectly. In order to improve the response efficiency of core networks expansion construction, early warning of the core network elements capacity is necessary. Based on the integrated architecture of space and terrestrial network, multidimensional factors are considered in this paper, including the number of terminals, login users, and the rules of users' migration during holidays. Using artifical intelligence (AI) technologies, the registered users of the access and mobility management function (AMF), authorization users of the unified data management (UDM), protocol data unit (PDU) sessions of session management function (SMF) are predicted in combination with the number of login users, the number of terminals. Therefore, the core network elements capacity can be predicted in advance. The proposed method is proven to be effective based on the data from real network.
{"title":"Early Warning of Core Network Capacity in Space-Terrestrial Integrated Networks","authors":"Sai Han, Ao Li, Dongyue Zhang, Bin Zhu, Zelin Wang, Guangquan Wang, Jie Miao, Hongbing Ma","doi":"10.23919/jsee.2024.000072","DOIUrl":"https://doi.org/10.23919/jsee.2024.000072","url":null,"abstract":"With the rapid development of low-orbit satellite communication networks both domestically and internationally, space-terrestrial integrated networks will become the future development trend. For space and terrestrial networks with limited resources, the utilization efficiency of the entire space-terrestrial integrated networks resources can be affected by the core network indirectly. In order to improve the response efficiency of core networks expansion construction, early warning of the core network elements capacity is necessary. Based on the integrated architecture of space and terrestrial network, multidimensional factors are considered in this paper, including the number of terminals, login users, and the rules of users' migration during holidays. Using artifical intelligence (AI) technologies, the registered users of the access and mobility management function (AMF), authorization users of the unified data management (UDM), protocol data unit (PDU) sessions of session management function (SMF) are predicted in combination with the number of login users, the number of terminals. Therefore, the core network elements capacity can be predicted in advance. The proposed method is proven to be effective based on the data from real network.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"19 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.23919/jsee.2024.000089
Yuanyuan Nie, Zhigeng Fang, Sifeng Liu, Su Gao
Survivability is used to evaluate the ability of the satellite to complete the mission after failure, while the duration of maintaining performance is often ignored. An effective backup strategy can restore the constellation performance timely, and maintain good network communication performance in case of satellite failure. From the perspective of network utility, the low Earth orbit (LEO) satellite constellation survivable graphical evaluation and review technology (GERT) network with backup satellites is constructed. A network utility transfer function algorithm based on moment generating function and Mason formula is proposed, the network survivability evaluation models of on-orbit backup strategy and ground backup strategy are established. The survivable GERT model can deduce the expected maintenance time of LEO satellite constellation under different fault states and the network utility generated during the state maintenance period. The case analysis shows that the proposed survivable GERT model can consider the satellite failure rate, backup satellite replacement rate, maneuver control replacement ability and life requirement, and effectively determine the optimal survivable backup strategy for LEO satellite constellation with limited resources according to the expected network utility.
生存能力用于评价卫星在故障后完成任务的能力，而保持性能的持续时间往往被忽视。有效的备份策略可以及时恢复星座性能，并在卫星失效时保持良好的网络通信性能。从网络效用的角度出发，构建了具有备份卫星的低地球轨道（LEO）卫星星座可生存图形评估和审查技术（GERT）网络。提出了基于矩生成函数和 Mason 公式的网络效用转移函数算法，建立了在轨备份策略和地面备份策略的网络生存性评估模型。可生存的 GERT 模型可推导出不同故障状态下 LEO 卫星群的预期维护时间以及状态维护期内产生的网络效用。案例分析表明，所提出的可生存 GERT 模型能够综合考虑卫星故障率、备份卫星替换率、机动控制替换能力和寿命要求，根据预期网络效用有效确定资源有限的低地球轨道卫星星座的最优可生存备份策略。
{"title":"Survivability Model of LEO Satellite Constellation Based on GERT with Limited Backup Resources","authors":"Yuanyuan Nie, Zhigeng Fang, Sifeng Liu, Su Gao","doi":"10.23919/jsee.2024.000089","DOIUrl":"https://doi.org/10.23919/jsee.2024.000089","url":null,"abstract":"Survivability is used to evaluate the ability of the satellite to complete the mission after failure, while the duration of maintaining performance is often ignored. An effective backup strategy can restore the constellation performance timely, and maintain good network communication performance in case of satellite failure. From the perspective of network utility, the low Earth orbit (LEO) satellite constellation survivable graphical evaluation and review technology (GERT) network with backup satellites is constructed. A network utility transfer function algorithm based on moment generating function and Mason formula is proposed, the network survivability evaluation models of on-orbit backup strategy and ground backup strategy are established. The survivable GERT model can deduce the expected maintenance time of LEO satellite constellation under different fault states and the network utility generated during the state maintenance period. The case analysis shows that the proposed survivable GERT model can consider the satellite failure rate, backup satellite replacement rate, maneuver control replacement ability and life requirement, and effectively determine the optimal survivable backup strategy for LEO satellite constellation with limited resources according to the expected network utility.","PeriodicalId":50030,"journal":{"name":"Journal of Systems Engineering and Electronics","volume":"73 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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