Traditional satellite networks depend on the closed and planned architecture. Thus, there are many challenges such as configuration update, new communication and networking technologies introduction, truly-differentiated services provision, satellite network device interoperability, and the integration of satellite and terrestrial networks. Software-defined networking (SDN) has the features of flexibility, programmability, and logical centralization, which increases network resource utilization, simplifies network management, reduces operating cost, and promotes the evolution and innovation. In this paper, a new software-defined architecture for next-generation satellite networks, called SoftSpace, is presented. The concepts of network function virtualization, network virtualization, and software-defined radio are exploited in the SoftSpace to facilitate the incorporation of new applications, services, and satellite communication technologies. This can not only reduce the capital expenditures and operational expenditures but also integrate satellite networks with terrestrial networks seamlessly, as well as can improve the interoperability of satellite network devices. In addition, we discuss the challenges and solutions for network management. The necessary network management instruments including multi-layer controller architecture, cooperative traffic classification, and utility-optimal network virtualization are presented. Finally, we discuss the challenges and solutions for space networking. The software-defined space networking solutions including quality of experience-aware space routing, SDN-enabled hybrid fault recovery mechanism, and software-defined space mobility management are developed.

Software-Defined Next-Generation Satellite Networks: Architecture, Challenges, and Solutions

Satellite networks are drawing more and more attention, since they can provide various services to everywhere on the earth. Communication devices in satellites are typically powered by solar panels and battery cells, which are carefully designed to guarantee power supply and avoid deficiency. However, we find that unrestrained use of energy will cause a satellite to age quickly, because the number of recharge/discharge of battery cells is limited. Due to the extremely high cost of satellites, the development of energy-efficient satellite routing to save energy and prolong satellite lifetimes has become significantly important. In this paper, we do comprehensive studies. First, we model the power consumption of a space router, power supply by solar panels, and aging of battery cells formally. Second, we define the energy-efficient satellite routing (EESR) problem, and prove that the EESR problem is NP-hard. Then, we develop three algorithms to gradually solve the EESR problem. GreenSR-B is a baseline algorithm which computes link costs iteratively to compute a routing that minimizes the total recharge/discharge cycle number. GreenSR-A selects space routers to switch into sleep mode to improve energy conservation. GreenSR jointly considers energy efficiency and QoS requirements of path length and the maximum link utilization ratio. We evaluate our algorithms by simulations on a low earth orbit satellite network with real Internet usage traces. The results show that GreenSR can prolong the lifetime of satellite battery cells by more than 40%, with little increment in path length and a small link utilization ratio.

Towards Energy-Efficient Routing in Satellite Networks

It is a desirable goal to fuse satellite and ground integrated networks (SGINs) to improve the resource utilization efficiency. However, existing work did not consider how to integrate them as a whole network because they lack of function-configurable network management and efficient cooperation among satellite and ground networks. In this paper, we firstly propose a SDN-based network architecture, where resources in SGINs are managed and scheduled in the layered and on-demand way. Then, we formulate the dynamical cooperation transmission in SGINs as an optimization problem and prove its NP hardness. Finally, to realize deeper-level resource fusion, we propose an efficient transmission approach DEEPER (aDaptive satEllitE-ground cooPerativE tRasmission) based on dynamical cooperation among satellite and ground networks, which is network-aware and workload-driven. Comprehensive experiment results demonstrate that our approach outperforms related schemes in terms of network throughput, end-to-end delay, transmission quality and load balancing.

Dynamically Adaptive Cooperation Transmission among Satellite-Ground Integrated Networks

Satellite networks provide complete connectivity and worldwide data transmission capability for constructing the Internet of Things. However, because of the varying Internet of Things traffic densi...

https://journals.sagepub.com/doi/pdf/10.1177/1550147717692586

HGL: A hybrid global-local load balancing routing scheme for the Internet of Things through satellite networks:

In this paper, the topology configuration methods for heterogeneous optical satellite networks are investigated. Our objectives are to maximize weighted algebraic connectivity with respect to both network initialization and reconfiguration scenarios subject to onboard hardware constraints. The problems are not strictly convex and have been proven as NP-hard. In order to solve the problems in polynomial time, the original problems are relaxed to a convex optimization problem. Specifically, the relaxed problem is transformed to a positive semidefinite programming form, which can be solved exactly and more efficiently. Furthermore, based on the perturbation theory of matrices, we propose two greedy heuristic methods to deal with the initialization and reconfiguration case from the relaxed solutions, respectively. Simulation results show that the proposed algorithms are able to accomplish network initialization and reconfiguration correctly in the overwhelming majority of situations. The final sub-optimal solutions can also be obtained under low computational complexity.

Weighted Algebraic Connectivity Maximization for Optical Satellite Networks

We formalize the construction of fault blocks by a state transition model based on finite state automata. Based on the model, a boundary diffusion method is presented for the rectilinear-monotone orthogonal convex fault model such as the rectangular fault model and minimal-connected-component (MCC) faulty model, whereby an adaptive fault-tolerant routing algorithm, called X-Y boundary routing algorithm (X-YBRA), is presented for deadlock-free fault-tolerant adaptive routing outside the fault blocks. To improve the network resources utilization, we put forward a routing diffusion method in the fault block, which completely solves the routing problem in the fault block. The experiment result shows that the diffusion overhead of our method is far lower than that of the traditional routing algorithms such as distance vector and link state routing algorithms with the light loss in convergence time. For the occurrence and recovery of random faults, the expansion and shrinkage of the fault block are also discussed. Accordingly, the dynamic boundary and routing updating methods are put forward to respond to these cases. Based on these methods, we develop low earth orbit satellite networks into an adaptive fault-tolerant system in routing. Our works can be also applied to other 2D mesh networks such as the interconnect multiprocessor computer systems.

Dianjun Wang

Papers

Dynamic Fault-Tolerant Routing Based on FSA for LEO Satellite Networks