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Satellite edge computing (SEC) has become a revolutionary paradigm to improve the quality of service, reduce the pressure on satellite-terrestrial backhaul bandwidth and reduce the average response delay of task requests. In this paper, we propose a task offloading algorithm based on K-D3QN to meet the rapidly growing demand of ground users. This algorithm improves the DQN algorithm by incorporating a satellite resource clustering module, a DDQN algorithm, and a competitive network mechanism module. The offloading decision-making process comprehensively considers three optimization objectives: task latency, resource utilization, and load-balancing degree, to achieve dynamic multi-objective optimization. Experimental results shown that the algorithm significantly reduces task latency, improves resource utilization and load-balancing degree.

With satellite systems rapidly developing in multiple satellites, multiple tasks, and high-speed response speed requirements, existing computing techniques face the following challenges: insufficient computing power, limited computing resources, and weaker coordination ability. Meanwhile, most methods have more significant response speed and resource utilization limitations. To solve the above problem, we propose a distributed collaborative computing framework with a genetic algorithm-based task scheduling model (DCCF-GA), which can realize the collaborative computing between multiple satellites through genetic algorithm. Specifically, it contains two aspects of work. First, a distributed architecture of satellites is constructed where the main satellite is responsible for distribution and scheduling, and the computing satellite is accountable for completing the task. Then, we presented a genetic algorithm-based task scheduling model that enables multiple satellites to collaborate for completing the tasks. Experiments show that the proposed algorithm has apparent advantages in completion time and outperforms other algorithms in resource efficiency.

We investigate the capabilities of space-based gravitational-wave detector networks, specifically Taiji and LISA, to measure the anisotropies in stochastic gravitational-wave background (SGWB), which are characterized by the angular power spectrum. We find that a detector network can improve the measurement precision of anisotropies by at most fourteen orders of magnitude, depending on the angular multipoles. By doing so, we can enhance our understanding of the physical origins of SGWB, both in astrophysical and cosmological contexts. We assess the prospects of the detector networks for measuring the parameters of angular power spectrum. We further find an inevitable effect of cosmic variance, which can be suppressed by a better angular resolution, strengthening the importance of configuring detector networks. Our findings also suggest a potential detection of the kinematic dipole due to Doppler boosting of SGWB.

This paper proposes a cloud-edge collaborative method for operational situation assessment to ensure the efficient and reliable operation of space-based information networks. By analyzing time-varying network topology characteristics, we establish a 14-dimensional assessment factor system that can characterize the operational situation of space-based information networks. Considering the resource constraints of satellites, traditional on-orbit assessment methods often lead to high latency and excessive resource consumption. A cloud-edge collaborative situation assessment method is introduced to enhance assessment efficiency. The proposed method first applies principal component analysis for dimensionality reduction, followed by pre-labeling situational factor data using an improved K-means clustering algorithm. The on-orbit assessment of individual satellites is then performed using a particle swarm optimization-support vector machine algorithm. Finally, a fusion assessment of the space-based information networks is conducted at the ground cloud center, incorporating situation weighting factors. Experimental results demonstrate that the proposed cloud-edge collaborative method improves assessment accuracy by 13% compared to baseline methods, significantly reduces average completion time, and maintains stable performance in large-scale satellite constellations.

With the rapid development of communications technology, the space-based information network (SBIN) is increasingly threatened by the outside world. Dynamic changes in any part of its interior can cause the collapse of the entire network. Therefore, research on the invulnerability of SBIN has become an urgent need to promote the economic development of our country and improve the living standards of our people. To this end, this paper has carried out research on the node-attacked invulnerability of SBIN based on the complex network theory. First, based on the model of SBIN, the internal parameters of the network are analyzed theoretically based on complex networks. Second, the paper proposes an improved tree attack strategy to analyze the invulnerability of SBIN, which constitutes a problem where the traditional attack strategy has a low invulnerability and the connected edge cannot fully realize the network function. Then, based on the improved tree attack strategy algorithm, this paper optimizes the invulnerability of SBIN by constructing four different edge-increasing strategies. Through the research, the LDF edge-increasing strategy makes the entire network flatter and can effectively improve the network’s ability to resist destruction. The research of invulnerability based on the complex network has a certain technical support and theoretical guidance for the construction of a reasonable and stable SBIN.

Facing the growing high data rate and large communication capacity demands, optical communications are widely recognized to be used to implement satellite communications. For a space-based optical backbone network, an appropriately designed protocol stack is important. In this paper, we proposed a protocol stack that is suitable for a space-based optical backbone network. Following this, we then used software to simulate this stack, built a hardware platform to test it, and finally, analyzed the results. The results showed that the proposed protocol stack was well designed to provide efficient control and management of the space-based optical backbone network. It could improve management efficiency by collecting resources and automatically calculating and building route paths. It could also facilitate data forwarding in intermediate satellite nodes with limited source and power, by using an advanced orbiting systems (AOS) frame switching scheme to avoid unnecessary processes, such as unpacking, upper-layer processing and repacking for passing services. The protocol stack could also support the use of unidirectional links to improve the link resource utilization. Finally, it could also provide transparent transmission for different kinds of services.

This chapter contains sections titled: Introduction Overview of survivability and resiliency Survivability framework Introduction to stochastic Petri nets (SPNs) SPNs for spacecraft modeling and survivability analysis Appendix: SPN model of the space‐based network (SBN) in Figure 8.6 and its schematic explanation

To ensure the authenticity and integrity of bundles, the in-transit PDUs of bundle protocol (BP) in space delay/disruption-tolerant networks (DTNs), the bundle security protocol specification (IRTF RFC6257) suggested using a digital signature directly over each bundle. However, when bundle fragment services are needed, this mechanism suffers from heavy computational costs, bandwidth overheads and energy consumption. In this paper, we address the fragment authentication issue for BP by exploiting the combination of RS error correction and erasure codes with the help of batch transmission characteristic of DTNs. The RS error correction and erasure codes are adopted to allow the receivers to locate the false/injected fragments and reconstruct the only one signature shared by all fragments of a bundle, even if some other fragments are lost or routed to a different path. Getting only partial authentic fragments, a DTN node is able to detect and filter the false/injected fragments, and authenticate the origin of a bundle as well. Such an approach tolerates high delays, unexpected link disruption and the BP nature of routing fragments of the same bundle possibly via different paths. The performance analysis demonstrates that both of our schemes, which follow our generic idea based on RS codes, significantly reduce bandwidth overheads and computational costs as compared to the prior works.

In the coming decades, the space-based gravitational-wave (GW) detectors such as Taiji, TianQin, and LISA are expected to form a network capable of detecting millihertz GWs emitted by the mergers of massive black hole binaries (MBHBs). In this work, we investigate the potential of GW standard sirens from the Taiji-TianQin-LISA network in constraining cosmological parameters. For the optimistic scenario in which electromagnetic (EM) counterparts can be detected, we predict the number of detectable bright sirens based on three different MBHB population models, i.e., pop III, Q3d, and Q3nod. Our results show that the Taiji-TianQin-LISA network alone could achieve a constraint precision of 0.9% for the Hubble constant, meeting the standard of precision cosmology. Moreover, the Taiji-TianQin-LISA network could effectively break the cosmological parameter degeneracies generated by the CMB data, particularly in the dynamical dark energy models. When combined with the CMB data, the joint CMB+Taiji-TianQin-LISA data offer σ ( w ) = 0.036 in the w CDM model, which is close to the latest constraint result obtained from the CMB+SN data. We also consider a conservative scenario in which EM counterparts are not available. Due to the precise sky localizations of MBHBs by the Taiji-TianQin-LISA network, the constraint precision of the Hubble constant is expected to reach 1.2%. In conclusion, the GW standard sirens from the Taiji-TianQin-LISA network will play a critical role in helping solve the Hubble tension and shedding light on the nature of dark energy.

Robust and accurate line segment matching remains a critical challenge in stereo vision, particularly in space-based applications where weak texture, structural symmetry, and strong illumination variations are common. This paper presents a multi-constraint progressive matching framework that integrates epipolar geometry, coplanarity verification, local homography, angular consistency, and distance-ratio invariance to establish reliable line correspondences. A unified cost matrix is constructed by quantitatively encoding these geometric residuals, enabling comprehensive candidate evaluation. To ensure global consistency and suppress mismatches, the final assignment is optimized using a Hungarian algorithm under one-to-one matching constraints. Extensive experiments on a wide range of stereo image pairs demonstrate that the proposed method consistently outperforms several advanced conventional approaches in terms of accuracy, robustness, and computational efficiency, as evidenced by both quantitative and qualitative evaluations.