为在月球建立长期驻留的月面科研基地,实现局部网络的通信覆盖,提出了月球通信塔(lunar communication tower,LCT)的模型设计方法和多基站的部署方案。通过对月面探测任务与月表多设施通信网络的需求分析,设计了LCT的功能模块和模型结...为在月球建立长期驻留的月面科研基地,实现局部网络的通信覆盖,提出了月球通信塔(lunar communication tower,LCT)的模型设计方法和多基站的部署方案。通过对月面探测任务与月表多设施通信网络的需求分析,设计了LCT的功能模块和模型结构。引入基于地理信息的覆盖场强预测模型,结合月表地形对通信链路的损耗影响,评估了多基站通信塔的有效覆盖与传输速率指标。在部署方案上,首先,在月球南极光照区范围内采用遍历法得到覆盖平均场强最大的主基站部署位置;随后,采用遗传算法最大化主基站半径10 km范围内的覆盖场强,对月球表面特定区域进行搜索,获取多个副基站的最佳部署位置;最后,针对集中式和分布式通信塔主、副基站的部署方案,进行了对应于CCSDS Proximity-1协议、长期演进(long term evolution,LTE)、Wi-Fi制式下覆盖性和传输速率的仿真分析,充分验证了月表多设施通信网络建设的可行性。展开更多
Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content deliver...Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.展开更多
Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In exist...Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.展开更多
文摘为在月球建立长期驻留的月面科研基地,实现局部网络的通信覆盖,提出了月球通信塔(lunar communication tower,LCT)的模型设计方法和多基站的部署方案。通过对月面探测任务与月表多设施通信网络的需求分析,设计了LCT的功能模块和模型结构。引入基于地理信息的覆盖场强预测模型,结合月表地形对通信链路的损耗影响,评估了多基站通信塔的有效覆盖与传输速率指标。在部署方案上,首先,在月球南极光照区范围内采用遍历法得到覆盖平均场强最大的主基站部署位置;随后,采用遗传算法最大化主基站半径10 km范围内的覆盖场强,对月球表面特定区域进行搜索,获取多个副基站的最佳部署位置;最后,针对集中式和分布式通信塔主、副基站的部署方案,进行了对应于CCSDS Proximity-1协议、长期演进(long term evolution,LTE)、Wi-Fi制式下覆盖性和传输速率的仿真分析,充分验证了月表多设施通信网络建设的可行性。
基金supported by National Natural Sciences Foundation of China(No.62271165,62027802,61831008)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030297,2021A1515011572)Shenzhen Science and Technology Program ZDSYS20210623091808025,Stable Support Plan Program GXWD20231129102638002.
文摘Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.
基金supported by National Natural Sciences Foundation of China(No.62271165,62027802,62201307)the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030297)+2 种基金the Shenzhen Science and Technology Program ZDSYS20210623091808025Stable Support Plan Program GXWD20231129102638002the Major Key Project of PCL(No.PCL2024A01)。
文摘Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.