Low Earth Orbit Satellite Networks Research Articles

A Load Balancing Routing Strategy for LEO Satellite Network

The LEO network composed of massive satellite nodes is a hot research field at present. In such a network, the problem of load balancing should be reconsidered due to the large number of satellite nodes, the frequently changing topology, and the uneven distribution of global ground users. To solve such problem, a selective iterative Dijkstra algorithm (SIDA) is proposed to optimize the path finding process by reducing the reuse frequency of nodes. On the basis of SIDA, a selective split load balancing strategy (SSLB) is proposed to solve the link congestion problem in low latitude LEO network. SSLB is a distributed strategy, which diverts the traffic flow of congestion nodes to neighboring nodes. SSLB reduces the burden of neighbor nodes, which need the less demand of computing resources and signaling interaction. Simulation results show that SIDA reduces the number of congestion links and balances the load distribution, while SSLB can effectively suppress the number of new congestion links after traffic diversion. These algorithms provide a load balancing solution for LEO satellite network.

Multisatellite Cooperative Random Access Scheme in Low Earth Orbit Satellite Networks

Multisatellite cooperative random access (MSC-RA) scheme is proposed in low earth orbit (LEO) satellite networks. In the scheme, a packet structure based on single carrier interleaved frequency division multiple access (SC-IFDMA) is designed to overcome the effect of users’ propagation delays on the received signals at satellite nodes, which ensures the synchronization of received signals. The transmission model from multiple terminals to multiple satellite nodes in a slot can be equivalent to a virtual multi-input multioutput model, and MSC detection is employed to decode multiple collided packets. The MSC detection can be applied to slotted ALOHA (SA), contention resolution diversity slotted ALOHA (CRDSA), CRDSA-3, and irregular repetition slotted ALOHA (IRSA) protocols, which are dubbed MSC-SA, MSC-CRDSA, MSC-CRDSA-3, and MSC-IRSA, respectively. At the gateway station, the MSC detection and iterative interference cancellation processing are alternately conducted for multiple collided packets at satellite nodes. The performance of these MSC-RA schemes is evaluated via mathematical analysis and computer simulation in terms of throughput, stability and energy efficiency. Simulation results show that MSC-SA, MSC-CRDSA, MSC-CRDSA-3, and MSC-IRSA schemes significantly outperform conventional ones, and the MSC-CRDSA scheme is superior to MSC-SA, MSC-CRDSA-3 and MSC-IRSA schemes.

A Two-Hops State-Aware Routing Strategy Based on Deep Reinforcement Learning for LEO Satellite Networks

Low Earth Orbit (LEO) satellite networks can provide complete connectivity and worldwide data transmission capability for the internet of things. However, arbitrary flow arrival and uneven traffic load among areas bring about unbalanced traffic distribution over the LEO constellation. Therefore, the routing strategy in LEO networks should have the ability to adjust routing paths based on changes in network status adaptively. In this paper, we propose a Two-Hops State-Aware Routing Strategy Based on Deep Reinforcement Learning (DRL-THSA) for LEO satellite networks. In this strategy, each node only needs to obtain the link state within the range of two-hop neighbors, and the optimal next-hop node can be output. The link state is divided into three levels, and the traffic forwarding strategy for each level is proposed, which allows DRL-THSA to cope with link outage or congestion. The Double-Deep Q Network (DDQN) is proposed in DRL-THSA to figure out the optional next hop by inputting the two-hops link states. The DDQN is analyzed from three aspects: model setting, training process and running process. The effectiveness of DRL-THSA, in terms of end-to-end delay, throughput, and packet drop rate, is verified via a set of simulations using the Network Simulator 3 (NS3).

A Dynamic Channel Reservation Strategy Based on Priorities of Multi-Traffic and Multi-User in LEO Satellite Networks

In Low Earth Orbit (LEO) satellite networks, it is a challenge to allocate the limited resources to meet the needs of different calls. In this paper, a dynamic channel reservation strategy based on priorities of multi-traffic and multi-user in LEO satellite networks is proposed. The dynamic admission threshold reserved for different calls is the key of this strategy. Firstly, the traffic prediction model based on LEO satellite mobility is established. Then the channel allocation model is built on the Markov process. Finally, the reserved admission thresholds are dynamically changed according to the predicted traffic. And the calculation of the admission thresholds is solved by the genetic algorithm. The simulation results show that the proposed strategy not only meets the needs of calls of different type traffic and different level users, but also improves the overall quality of service in LEO satellite networks.

A DTN Routing Scheme for LEO Satellites Topology

In delay/disruption-tolerant satellite networks, the existing routing algorithms have problems of long transmission delay, high packet loss rate, excessive network overhead and other issues. In the view of these shortcomings, an improved contact graph routing algorithm, ICGR, is proposed in this paper. Firstly, the impact of queuing delay is considered by defining a queue factor and proposing a queue scheduling mechanism in routing calculation; secondly, the effects of contact’s remaining capacity are taken into account to avoid the selected path being unable to forward the messages; thirdly, routing update mechanism is optimized by designing a message path update factor to strike a balance between real-time updates of transmission and resource consumption; finally, a LEO satellite network simulation platform is built with OPNET to verify the performance of this algorithm. Simulation results show that the ICGR, compared with the ED and CGR algorithm, has advantage in packet delivery rate, average transmission delay and network overhead.

Constellation Multi-Objective Optimization Design Based on QoS and Network Stability in LEO Satellite Broadband Networks

Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

Load-Balancing Routing Algorithm Based on Segment Routing for Traffic Return in LEO Satellite Networks

To tackle the network congestion problem caused by ground gateway stations arranged within a limited area in low earth orbit (LEO) satellite networks, a routing algorithm based on segment routing for traffic return is proposed. Light and heavy load zones are dynamically divided according to the relative position relationship between gateways and the reverse slot. The pre-balancing shortest path algorithm is used in the light load zone, and the minimum weight path defined by congestion index is the routing rule in the heavy load zone. Then, the consistent forwarding is performed referring to segment routing in all zones. Simulation conditions are different sizes of heavy load zone, different traffic density distributions, and different traffic demands. Simulation results confirm that the load-balancing performance is improved significantly with the extension of the heavy load zone size in terms of the average rejection ratio, the average relative throughput, the maximum link utilization, and the average delay. The proposed algorithm is an alternative solution and guidance for routing strategy in LEO satellite networks.

Multipath Cooperative Routing with Efficient Acknowledgement for LEO Satellite Networks

Multipath routing can significantly improve the network throughput and end-to-end (e2e) delay. Network coding based multipath routing removes the complicated coordination among multiple paths so that it further enhances data transmission efficiency. Traditional network coding based multipath routing protocols, however, are inefficient for Low Earth Orbit (LEO) satellite networks with the long link delay and regular network topology . Considering these characteristics, in this paper, we first formulate the multipath cooperative routing problem, then propose a Network Coding based Multipath Cooperative Routing (NCMCR) protocol for LEO satellite networks to improve the throughput. We propose source-based and destination-based multipath cooperative routing algorithms, which deliver different parts of a data flow along multiple link-disjoint paths dynamically and cooperatively. Furthermore, we design an efficient No-Stop-Wait ACK mechanism for our NCMCR protocol to accelerate the data transmission, where a source node continuously sends subsequent batches before it receives ACK messages for the batches sent previously. Under the proposed acknowledgement mechanism, we theoretically analyze the number of coded packets that should be sent and the transmission times of each batch for successfully decoding a batch. NS2-based simulation results demonstrate that our NCMCR outperforms the most related protocols.

A Satellite Handover Strategy Based on the Potential Game in LEO Satellite Networks

In a low earth orbit (LEO) satellite network, handover management across satellite spot beams needs to be addressed to decrease handover times while using network resources efficiently since the speed of LEO satellites is much higher than that of mobile nodes. In this paper, we propose a novel satellite handover strategy based on the potential game for mobile terminals in a LEO satellite communication network. To continue communication with the counterpart, the user has to switch among the covered LEO satellites. In a software-defined satellite network (SDSN) architecture, the satellite handover can be viewed as a bipartite graph. To balance the satellite network workload, we propose a terminal random-access algorithm based on the target of userspace maximization. The simulated handover conducted on a typical LEO satellite network, Iridium, corroborates the effectiveness of the proposed handover strategy.

Cross Layer Optimization of Wireless Control Links in the Software-Defined LEO Satellite Network

The low earth orbit (LEO) satellite network can benefit from software-defined networking (SDN) by lightening forwarding devices and improving service diversity. In order to apply SDN into the network, however, reliable SDN control links should be associated from satellite gateways to satellites, with the wireless and mobile properties of the network taken into account. Since these characteristics affect both control link association and gateway power allocation, we define a new cross layer SDN control link problem. To the best of our knowledge, this is the first attempt to explore the cross layer control link problem for the software-defined satellite network. A logically centralized SDN control framework constrained by maximum total power is introduced to enhance gateway power efficiency for control link setup. Based on the power control analysis of the problem, a power-efficient control link algorithm is developed, which establishes low latency control links with reduced power consumption. Along with the sensitivity analysis of the proposed control link algorithm, numerical results demonstrate low latency and high reliability of control links established by the algorithm, ultimately suggesting the feasibility, both technical and economical, of the software-defined LEO satellite network.

Adaptive Packet-Length Assisted Random Access Scheme in LEO Satellite Network

A new adaptive packet-length assisted random access (RA) scheme is proposed to improve the performance of the RA system in LEO satellite network. In the scheme, the lengths of data packets are adaptively selected with different modulation and coding schemes (MCSs) according to the transmission quality of the LEO satellite link. Based on the adaptive packet length, the protocols based on advanced slotted ALOHA are modified and analyzed. The simulation results show that the throughput of the adaptive packet-length assisted CRDSA (APL-CRDSA) is about 1.5 times larger than that of the conventional CRDSA. The packet loss rate (PLR) performance and the energy efficiency performance of the APL-CRDSA are also greater than those of the conventional CRDSA.

Survivability Analysis of LEO Satellite Networks Based on Network Utility

The LEO satellite network is threatened by accidental faults, malicious attacks and other factors during its operation. This paper proposed a model of survivability evaluation based on network utility. First, calculate the communication performance indicators of delay, congestion rate and throughput of LEO satellite networks by different types of queue theory birth and death model; then, combined these performance indicators with reliability and cost planning to construct network utility function which is used for evaluating the survivability of LEO satellite networks under natural failure, random attack, deliberate attack and saturation attack modes. The case study shows that: the greater the arrival rate of natural faults, the shorter the time required to descend to the network utility threshold, the network is more vulnerable to intentional attacks; the survivability can’t be enhanced by adding buffers; the importance of nodes and links is related to the proportion of real-time and non-real-time services and the traffic of different satellite coverage areas.

Time-Sliced Flexible Resource Allocation for Optical Low Earth Orbit Satellite Networks

In future optical satellite networks with various service requirements, the bandwidth of a single traffic request occupies part of an inter-satellite link (ISL) channel capacity, thus leading to a greater demand for flexible resource allocation. The switching scheme is the most important determinant for flexible resource allocation in optical satellite networks, whereas the widely used optical switching techniques, including wavelength switching (WS) and electronic packet switching (EPS), have their own drawbacks such as bandwidth underutilization and high power consumption. In this paper, we utilize optical time slice switching (OTSS) to provide enormous transparent fine-grained connections for various traffic requests. To implement OTSS into low earth orbit (LEO) satellite networks, where the lengths of inter-orbit ISLs vary along time, we propose a distance-varying routing and time slice allocation (DV-RTSA) scheme. The simulation results demonstrate that the OTSS-based DV-RTSA scheme not only utilizes less active transponders when compared with the traditional schemes, but also achieves a significant throughput increase over the WS-based scheme and reaches the level of the EPS-based scheme exempting from its defects.

Agent-Based Load Balancing and Qos Routing for Leo Satellite Networks

This paper proposes and evaluates the Agent-based load balancing and QoS routing (ALBQR) in the low earth orbit (LEO) satellite networks. Two kinds of agents are designed. Stationary agents located at the satellites calculate link cost using the sum of propagation and queuing delays, employ FARIMA model to predict the traffic of satellite node, modify the link cost based on the predicted traffic. Mobile agents migrate among satellites to gather link status information, notify stationary agents to update routing tables and reserve resource. Mobile agents carry user’s delay, bandwidth and packet loss rate, explore the routing path of satisfy the lowest path cost and QoS constraints. Through simulations on an Iridium satellite network, ALBQR is shown to achieve a balanced traffic distribution among satellites, provide better throughput, decrease packet loss and average end-to-end delay.

Regional Cooperative Authentication Protocol for LEO Satellite Networks Based on Consensus Mechanism

Regional Cooperative Authentication Protocol for LEO Satellite Networks Based on Consensus Mechanism

Hybrid-Traffic-Detour based load balancing for onboard routing in LEO satellite networks

To deal with the dynamic and imbalanced traffic requirements in Low Earth Orbit satellite networks, several distributed load balancing routing schemes have been proposed. However, because of the lack of global view, these schemes may lead to cascading congestion in regions with high volume of traffic. To solve this problem, a Hybrid-Traffic-Detour based Load Balancing Routing (HLBR) scheme is proposed, where a Long-Distance Traffic Detour (LTD) method is devised and coordinates with distributed traffic detour method to perform self-adaptive load balancing. The forwarding path of LTD is acquired by the Circuitous Multipath Calculation (CMC) based on prior geographical information, and activated by the LTD-Shift-Trigger (LST) through real-time congestion perception. Simulation results show that the HLBR can mitigate cascading congestion and achieve efficient traffic distribution.

Temporal Centrality-Balanced Traffic Management for Space Satellite Networks

Structural centrality metrics of the networks are important features to identify central nodes or links, to assess network vulnerability against removal of nodes or links, and to manage or control the network traffic to reduce the network congestion. Classic graph-based centrality metrics are not effective in dynamic space satellite networks due to the changing connectivity and they cannot effectively capture important temporal properties. In this paper, we employ a new technique called time-varying graphs (TVGs) to express temporal concepts and definitions of space satellite networks and propose several temporal centrality metrics in order to account for the temporal features of the networks. To calculate these temporal centrality metrics, we adopt a modified matrix multiplication algorithm to find the shortest journeys between nodes in the TVG. A temporal centrality-balanced traffic management scheme is further developed to enhance the network performance, which is integrated into a temporal centrality-balanced routing algorithm. To show the performance of the proposed centrality metrics and centrality balanced routing algorithm, we conduct some experiments performed on a scenario of the LEO satellite network. The simulation results show that the proposed centrality metrics are more powerful to analyze the evolution of time-varying centrality and vulnerability of space satellite networks than topological adaptation of vanilla centrality methods. Besides, the proposed centrality-balanced routing algorithm reaches the superior quality values of the network performance (in terms of several factors) in comparison with those attained by the traditional shortest journeys routing algorithm and proves to be more powerful to support the high traffic load.

Distributed Routing Strategy Based on Machine Learning for LEO Satellite Network

As the indispensable supplement of terrestrial communications, Low Earth Orbit (LEO) satellite network is the crucial part in future space‐terrestrial integrated networks because of its unique advantages. However, the effective and reliable routing for LEO satellite network is an intractable task due to time‐varying topology, frequent link handover, and imbalanced communication load. An Extreme Learning Machine (ELM) based distributed routing (ELMDR) strategy was put forward in this paper. Considering the traffic distribution density on the surface of the earth, ELMDR strategy makes routing decision based on traffic prediction. For traffic prediction, ELM, which is a fast and efficient machine learning algorithm, is adopted to forecast the traffic at satellite node. For the routing decision, mobile agents (MAs) are introduced to simultaneously and independently search for LEO satellite network and determine routing information. Simulation results demonstrate that, in comparison to the conventional Ant Colony Optimization (ACO) algorithm, ELMDR not only sufficiently uses underutilized link, but also reduces delay.

A load balanced routing algorithm based on congestion prediction for LEO satellite networks

This paper presents a load balancing routing algorithm based on congestion prediction (LBRA-CP) so as to realize an efficient load balancing over the entire Low Earth Orbit satellite networks. A multi-objective optimization model is built, which not only adopts modifying factor to adjust path cost, but also uses congestion prediction to foresee inter-satellite link congestion. Then an ant colony algorithm is utilized to solve this model, resulting in finding an optimal path for every connection request. Meanwhile, in order to improve the reliability of LBRA-CP, the valve of the pheromone evaporation coefficient is discussed in this paper. The performance is measured by the receiver’s throughput, the link utilization and the end-to-end delay. Simulation results show that LBRA-CP performs well in balancing traffic load and increases the receiver’s throughput. Meanwhile, the end-to-end delay can meet the requirement of video transmission.

Routing Algorithm with Virtual Topology Toward to Huge Numbers of LEO Mobile Satellite Network Based on SDN

SDN network is a dynamic, controllable, cost-effective and adaptable system. It is suitable for communication networks with high bandwidth and high dynamic characteristics. Therefore, combining SDN ideas with the new generation of LEO satellite networks can achieve more flexible monitoring and management of the network, and can make the network expansion more convenient. Joint the Depth-First-Search (DFS) idea and Dijkstra algorithm for the huge numbers of LEO mobile satellite network based on SDN is proposed to improve the computational efficiency and the reliability of calculation result. Moreover, the communication performance of space-based network based on SDN and traditional space-based network is compared and analyzed. The simulation results show that the huge numbers of LEO mobile satellite network based on SDN breaks through the performance limitations of the traditional network architecture, and it can achieve better performance of the network.